diff --git a/.eslintignore b/.eslintignore
new file mode 100644
index 0000000..4f8fb4f
--- /dev/null
+++ b/.eslintignore
@@ -0,0 +1,3 @@
+node_modules
+dist
+jest.config.js
diff --git a/.eslintrc b/.eslintrc
new file mode 100644
index 0000000..4afa5b0
--- /dev/null
+++ b/.eslintrc
@@ -0,0 +1,17 @@
+{
+  "parser": "@typescript-eslint/parser",
+  "parserOptions": {
+    "ecmaVersion": 12,
+    "sourceType": "module"
+  },
+  "plugins": ["@typescript-eslint"],
+  "extends": [
+    "eslint:recommended",
+    "plugin:@typescript-eslint/recommended",
+    "prettier"
+  ],
+  "rules": {},
+  "env": {
+    "es2021": true
+  }
+}
diff --git a/.prettierrc b/.prettierrc
new file mode 100644
index 0000000..435f64a
--- /dev/null
+++ b/.prettierrc
@@ -0,0 +1,5 @@
+{
+  "semi": false,
+  "singleQuote": false,
+  "arrowParens": "avoid"
+}
diff --git a/jest.config.js b/jest.config.js
index 39ee932..d86d036 100644
--- a/jest.config.js
+++ b/jest.config.js
@@ -1,14 +1,10 @@
 /** @type {import('ts-jest').JestConfigWithTsJest} */
 module.exports = {
-  preset: 'ts-jest',
-  testEnvironment: 'node',
+  preset: "ts-jest",
+  testEnvironment: "node",
   collectCoverage: true,
-  coverageDirectory: 'coverage',
-  testPathIgnorePatterns: [
-    '/node_modules/',
-  ],
-  preset: 'ts-jest',
-  roots: [
-    '<rootDir>/src',
-  ]
-};
+  coverageDirectory: "coverage",
+  testPathIgnorePatterns: ["/node_modules/"],
+  preset: "ts-jest",
+  roots: ["<rootDir>/src"],
+}
diff --git a/package-lock.json b/package-lock.json
index 95986a6..e546632 100644
--- a/package-lock.json
+++ b/package-lock.json
@@ -21,7 +21,12 @@
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         "@types/jest": "29.5.9",
+        "@typescript-eslint/eslint-plugin": "6.13.2",
+        "@typescript-eslint/parser": "6.13.2",
+        "eslint": "8.55.0",
+        "eslint-config-prettier": "9.1.0",
         "pino-pretty": "10.2.3",
+        "prettier": "3.1.0",
         "ts-jest": "29.1.1"
       }
     },
@@ -35,6 +40,15 @@
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       }
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+      "resolved": "https://registry.npmjs.org/@aashutoshrathi/word-wrap/-/word-wrap-1.2.6.tgz",
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+      "dev": true,
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       "version": "2.2.1",
       "resolved": "https://registry.npmjs.org/@ampproject/remapping/-/remapping-2.2.1.tgz",
@@ -725,6 +739,162 @@
         "@jridgewell/sourcemap-codec": "^1.4.10"
       }
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+      "resolved": "https://registry.npmjs.org/@eslint-community/eslint-utils/-/eslint-utils-4.4.0.tgz",
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+      "dev": true,
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+      },
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+      },
+      "peerDependencies": {
+        "eslint": "^6.0.0 || ^7.0.0 || >=8.0.0"
+      }
+    },
+    "node_modules/@eslint-community/regexpp": {
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+      "resolved": "https://registry.npmjs.org/@eslint-community/regexpp/-/regexpp-4.10.0.tgz",
+      "integrity": "sha512-Cu96Sd2By9mCNTx2iyKOmq10v22jUVQv0lQnlGNy16oE9589yE+QADPbrMGCkA51cKZSg3Pu/aTJVTGfL/qjUA==",
+      "dev": true,
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+      }
+    },
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+      "resolved": "https://registry.npmjs.org/@humanwhocodes/module-importer/-/module-importer-1.0.1.tgz",
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+      "dev": true,
+      "engines": {
+        "node": ">=12.22"
+      },
+      "funding": {
+        "type": "github",
+        "url": "https://github.com/sponsors/nzakas"
+      }
+    },
+    "node_modules/@humanwhocodes/object-schema": {
+      "version": "2.0.1",
+      "resolved": "https://registry.npmjs.org/@humanwhocodes/object-schema/-/object-schema-2.0.1.tgz",
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+      "dev": true
+    },
     "node_modules/@istanbuljs/load-nyc-config": {
       "version": "1.1.0",
       "resolved": "https://registry.npmjs.org/@istanbuljs/load-nyc-config/-/load-nyc-config-1.1.0.tgz",
@@ -1090,6 +1260,41 @@
         "@jridgewell/sourcemap-codec": "^1.4.14"
       }
     },
+    "node_modules/@nodelib/fs.scandir": {
+      "version": "2.1.5",
+      "resolved": "https://registry.npmjs.org/@nodelib/fs.scandir/-/fs.scandir-2.1.5.tgz",
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+      "dev": true,
+      "dependencies": {
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+        "run-parallel": "^1.1.9"
+      },
+      "engines": {
+        "node": ">= 8"
+      }
+    },
+    "node_modules/@nodelib/fs.stat": {
+      "version": "2.0.5",
+      "resolved": "https://registry.npmjs.org/@nodelib/fs.stat/-/fs.stat-2.0.5.tgz",
+      "integrity": "sha512-RkhPPp2zrqDAQA/2jNhnztcPAlv64XdhIp7a7454A5ovI7Bukxgt7MX7udwAu3zg1DcpPU0rz3VV1SeaqvY4+A==",
+      "dev": true,
+      "engines": {
+        "node": ">= 8"
+      }
+    },
+    "node_modules/@nodelib/fs.walk": {
+      "version": "1.2.8",
+      "resolved": "https://registry.npmjs.org/@nodelib/fs.walk/-/fs.walk-1.2.8.tgz",
+      "integrity": "sha512-oGB+UxlgWcgQkgwo8GcEGwemoTFt3FIO9ababBmaGwXIoBKZ+GTy0pP185beGg7Llih/NSHSV2XAs1lnznocSg==",
+      "dev": true,
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+        "fastq": "^1.6.0"
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       "resolved": "https://registry.npmjs.org/@sinclair/typebox/-/typebox-0.27.8.tgz",
@@ -6941,6 +7146,12 @@
         "pretty-format": "^29.0.0"
       }
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+      "resolved": "https://registry.npmjs.org/@types/json-schema/-/json-schema-7.0.15.tgz",
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+      "dev": true
+    },
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       "resolved": "https://registry.npmjs.org/@types/node/-/node-20.10.0.tgz",
@@ -6958,6 +7169,12 @@
         "form-data": "^4.0.0"
       }
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+      "resolved": "https://registry.npmjs.org/queue-microtask/-/queue-microtask-1.2.3.tgz",
+      "integrity": "sha512-NuaNSa6flKT5JaSYQzJok04JzTL1CA6aGhv5rfLW3PgqA+M2ChpZQnAC8h8i4ZFkBS8X5RqkDBHA7r4hej3K9A==",
+      "dev": true,
+      "funding": [
+        {
+          "type": "github",
+          "url": "https://github.com/sponsors/feross"
+        },
+        {
+          "type": "patreon",
+          "url": "https://www.patreon.com/feross"
+        },
+        {
+          "type": "consulting",
+          "url": "https://feross.org/support"
+        }
+      ]
+    },
     "node_modules/quick-format-unescaped": {
       "version": "4.0.4",
       "resolved": "https://registry.npmjs.org/quick-format-unescaped/-/quick-format-unescaped-4.0.4.tgz",
@@ -9875,6 +11006,54 @@
         "node": ">=10"
       }
     },
+    "node_modules/reusify": {
+      "version": "1.0.4",
+      "resolved": "https://registry.npmjs.org/reusify/-/reusify-1.0.4.tgz",
+      "integrity": "sha512-U9nH88a3fc/ekCF1l0/UP1IosiuIjyTh7hBvXVMHYgVcfGvt897Xguj2UOLDeI5BG2m7/uwyaLVT6fbtCwTyzw==",
+      "dev": true,
+      "engines": {
+        "iojs": ">=1.0.0",
+        "node": ">=0.10.0"
+      }
+    },
+    "node_modules/rimraf": {
+      "version": "3.0.2",
+      "resolved": "https://registry.npmjs.org/rimraf/-/rimraf-3.0.2.tgz",
+      "integrity": "sha512-JZkJMZkAGFFPP2YqXZXPbMlMBgsxzE8ILs4lMIX/2o0L9UBw9O/Y3o6wFw/i9YLapcUJWwqbi3kdxIPdC62TIA==",
+      "dev": true,
+      "dependencies": {
+        "glob": "^7.1.3"
+      },
+      "bin": {
+        "rimraf": "bin.js"
+      },
+      "funding": {
+        "url": "https://github.com/sponsors/isaacs"
+      }
+    },
+    "node_modules/run-parallel": {
+      "version": "1.2.0",
+      "resolved": "https://registry.npmjs.org/run-parallel/-/run-parallel-1.2.0.tgz",
+      "integrity": "sha512-5l4VyZR86LZ/lDxZTR6jqL8AFE2S0IFLMP26AbjsLVADxHdhB/c0GUsH+y39UfCi3dzz8OlQuPmnaJOMoDHQBA==",
+      "dev": true,
+      "funding": [
+        {
+          "type": "github",
+          "url": "https://github.com/sponsors/feross"
+        },
+        {
+          "type": "patreon",
+          "url": "https://www.patreon.com/feross"
+        },
+        {
+          "type": "consulting",
+          "url": "https://feross.org/support"
+        }
+      ],
+      "dependencies": {
+        "queue-microtask": "^1.2.2"
+      }
+    },
     "node_modules/safe-buffer": {
       "version": "5.2.1",
       "resolved": "https://registry.npmjs.org/safe-buffer/-/safe-buffer-5.2.1.tgz",
@@ -9923,7 +11102,6 @@
       "resolved": "https://registry.npmjs.org/shebang-command/-/shebang-command-2.0.0.tgz",
       "integrity": "sha512-kHxr2zZpYtdmrN1qDjrrX/Z1rR1kG8Dx+gkpK1G4eXmvXswmcE1hTWBWYUzlraYw1/yZp6YuDY77YtvbN0dmDA==",
       "dev": true,
-      "peer": true,
       "dependencies": {
         "shebang-regex": "^3.0.0"
       },
@@ -9936,7 +11114,6 @@
       "resolved": "https://registry.npmjs.org/shebang-regex/-/shebang-regex-3.0.0.tgz",
       "integrity": "sha512-7++dFhtcx3353uBaq8DDR4NuxBetBzC7ZQOhmTQInHEd6bSrXdiEyzCvG07Z44UYdLShWUyXt5M/yhz8ekcb1A==",
       "dev": true,
-      "peer": true,
       "engines": {
         "node": ">=8"
       }
@@ -10062,7 +11239,6 @@
       "resolved": "https://registry.npmjs.org/strip-ansi/-/strip-ansi-6.0.1.tgz",
       "integrity": "sha512-Y38VPSHcqkFrCpFnQ9vuSXmquuv5oXOKpGeT6aGrr3o3Gc9AlVa6JBfUSOCnbxGGZF+/0ooI7KrPuUSztUdU5A==",
       "dev": true,
-      "peer": true,
       "dependencies": {
         "ansi-regex": "^5.0.1"
       },
@@ -10140,6 +11316,12 @@
         "node": ">=8"
       }
     },
+    "node_modules/text-table": {
+      "version": "0.2.0",
+      "resolved": "https://registry.npmjs.org/text-table/-/text-table-0.2.0.tgz",
+      "integrity": "sha512-N+8UisAXDGk8PFXP4HAzVR9nbfmVJ3zYLAWiTIoqC5v5isinhr+r5uaO8+7r3BMfuNIufIsA7RdpVgacC2cSpw==",
+      "dev": true
+    },
     "node_modules/thread-stream": {
       "version": "2.4.1",
       "resolved": "https://registry.npmjs.org/thread-stream/-/thread-stream-2.4.1.tgz",
@@ -10182,6 +11364,18 @@
       "resolved": "https://registry.npmjs.org/tr46/-/tr46-0.0.3.tgz",
       "integrity": "sha512-N3WMsuqV66lT30CrXNbEjx4GEwlow3v6rr4mCcv6prnfwhS01rkgyFdjPNBYd9br7LpXV1+Emh01fHnq2Gdgrw=="
     },
+    "node_modules/ts-api-utils": {
+      "version": "1.0.3",
+      "resolved": "https://registry.npmjs.org/ts-api-utils/-/ts-api-utils-1.0.3.tgz",
+      "integrity": "sha512-wNMeqtMz5NtwpT/UZGY5alT+VoKdSsOOP/kqHFcUW1P/VRhH2wJ48+DN2WwUliNbQ976ETwDL0Ifd2VVvgonvg==",
+      "dev": true,
+      "engines": {
+        "node": ">=16.13.0"
+      },
+      "peerDependencies": {
+        "typescript": ">=4.2.0"
+      }
+    },
     "node_modules/ts-jest": {
       "version": "29.1.1",
       "resolved": "https://registry.npmjs.org/ts-jest/-/ts-jest-29.1.1.tgz",
@@ -10300,6 +11494,18 @@
         }
       }
     },
+    "node_modules/type-check": {
+      "version": "0.4.0",
+      "resolved": "https://registry.npmjs.org/type-check/-/type-check-0.4.0.tgz",
+      "integrity": "sha512-XleUoc9uwGXqjWwXaUTZAmzMcFZ5858QA2vvx1Ur5xIcixXIP+8LnFDgRplU30us6teqdlskFfu+ae4K79Ooew==",
+      "dev": true,
+      "dependencies": {
+        "prelude-ls": "^1.2.1"
+      },
+      "engines": {
+        "node": ">= 0.8.0"
+      }
+    },
     "node_modules/type-detect": {
       "version": "4.0.8",
       "resolved": "https://registry.npmjs.org/type-detect/-/type-detect-4.0.8.tgz",
@@ -10443,7 +11649,6 @@
       "resolved": "https://registry.npmjs.org/which/-/which-2.0.2.tgz",
       "integrity": "sha512-BLI3Tl1TW3Pvl70l3yq3Y64i+awpwXqsGBYWkkqMtnbXgrMD+yj7rhW0kuEDxzJaYXGjEW5ogapKNMEKNMjibA==",
       "dev": true,
-      "peer": true,
       "dependencies": {
         "isexe": "^2.0.0"
       },
@@ -10550,7 +11755,6 @@
       "resolved": "https://registry.npmjs.org/yocto-queue/-/yocto-queue-0.1.0.tgz",
       "integrity": "sha512-rVksvsnNCdJ/ohGc6xgPwyN8eheCxsiLM8mxuE/t/mOVqJewPuO1miLpTHQiRgTKCLexL4MeAFVagts7HmNZ2Q==",
       "dev": true,
-      "peer": true,
       "engines": {
         "node": ">=10"
       },
diff --git a/package.json b/package.json
index 4f58a30..4af4818 100644
--- a/package.json
+++ b/package.json
@@ -7,6 +7,8 @@
     "typecheck": "tsc -b tsconfig.json",
     "typecheck:watch": "tsc -b tsconfig.json --watch",
     "build": "tsc -b tsconfig.json",
+    "lint": "eslint --ignore-path .eslintignore --ext .js,.ts .",
+    "format": "prettier --ignore-path .gitignore --write \"**/*.+(js|ts|json)\"",
     "clean": "tsc -b tsconfig.json --clean",
     "test": "jest",
     "prepare": "npm run build",
@@ -30,7 +32,12 @@
   },
   "devDependencies": {
     "@types/jest": "29.5.9",
+    "@typescript-eslint/eslint-plugin": "6.13.2",
+    "@typescript-eslint/parser": "6.13.2",
+    "eslint": "8.55.0",
+    "eslint-config-prettier": "9.1.0",
     "pino-pretty": "10.2.3",
+    "prettier": "3.1.0",
     "ts-jest": "29.1.1"
   }
 }
diff --git a/schema.json b/schema.json
index e79dc0c..46781b9 100644
--- a/schema.json
+++ b/schema.json
@@ -1,216 +1,189 @@
 {
-    "$id": "https://andrefs.com/schemas/2023/SemMeasures",
-    "$schema": "http://json-schema.org/draft-07/schema#",
-    "definitions": {
-        "DatasetProfile": {
-            "properties": {
-                "id": {
-                    "description": "An identifier for the dataset",
-                    "type": "string"
-                },
-                "metadata": {
-                    "$ref": "https://andrefs.com/schemas/2023/SemMeasures#/definitions/Metadata",
-                    "description": "Metadata for the dataset"
-                },
-                "originalInstructions": {
-                    "description": "The original instructions given to the annotators",
-                    "type": "string"
-                },
-                "partitions": {
-                    "description": "The partitions containing the dataset data",
-                    "items": {
-                        "$ref": "https://andrefs.com/schemas/2023/SemMeasures#/definitions/Partition"
-                    },
-                    "type": "array"
-                }
-            },
-            "required": [
-                "id",
-                "metadata",
-                "partitions"
-            ],
-            "type": "object"
+  "$id": "https://andrefs.com/schemas/2023/SemMeasures",
+  "$schema": "http://json-schema.org/draft-07/schema#",
+  "definitions": {
+    "DatasetProfile": {
+      "properties": {
+        "id": {
+          "description": "An identifier for the dataset",
+          "type": "string"
         },
-        "Metadata": {
-            "properties": {
-                "date": {
-                    "description": "The date the dataset was published",
-                    "pattern": "^[0-9]{4}(-[0-9]{2}(-[0-9]{2})?)?$",
-                    "type": "string"
-                },
-                "description": {
-                    "description": "A description of the dataset",
-                    "type": "string"
-                },
-                "downloadUrls": {
-                    "description": "URL(s) to download the dataset files",
-                    "items": {
-                        "format": "uri",
-                        "type": "string"
-                    },
-                    "type": "array"
-                },
-                "measureTypes": {
-                    "description": "Which type of measures are used to compare the words",
-                    "items": {
-                        "enum": [
-                            "relatedness",
-                            "similarity"
-                        ],
-                        "type": "string"
-                    },
-                    "type": "array"
-                },
-                "name": {
-                    "description": "The name of the dataset",
-                    "type": "string"
-                },
-                "papers": {
-                    "description": "Information about the scientific papers describing the dataset",
-                    "items": {
-                        "$ref": "https://andrefs.com/schemas/2023/SemMeasures#/definitions/Paper"
-                    },
-                    "type": "array"
-                },
-                "urls": {
-                    "description": "Web sites containing information about the dataset",
-                    "items": {
-                        "format": "uri",
-                        "type": "string"
-                    },
-                    "type": "array"
-                }
-            },
-            "required": [
-                "date",
-                "description",
-                "downloadUrls",
-                "measureTypes",
-                "name",
-                "papers",
-                "urls"
-            ],
-            "type": "object"
+        "metadata": {
+          "$ref": "https://andrefs.com/schemas/2023/SemMeasures#/definitions/Metadata",
+          "description": "Metadata for the dataset"
+        },
+        "originalInstructions": {
+          "description": "The original instructions given to the annotators",
+          "type": "string"
+        },
+        "partitions": {
+          "description": "The partitions containing the dataset data",
+          "items": {
+            "$ref": "https://andrefs.com/schemas/2023/SemMeasures#/definitions/Partition"
+          },
+          "type": "array"
+        }
+      },
+      "required": ["id", "metadata", "partitions"],
+      "type": "object"
+    },
+    "Metadata": {
+      "properties": {
+        "date": {
+          "description": "The date the dataset was published",
+          "pattern": "^[0-9]{4}(-[0-9]{2}(-[0-9]{2})?)?$",
+          "type": "string"
         },
-        "Paper": {
-            "properties": {
-                "title": {
-                    "description": "The title of the paper",
-                    "type": "string"
+        "description": {
+          "description": "A description of the dataset",
+          "type": "string"
+        },
+        "downloadUrls": {
+          "description": "URL(s) to download the dataset files",
+          "items": {
+            "format": "uri",
+            "type": "string"
+          },
+          "type": "array"
+        },
+        "measureTypes": {
+          "description": "Which type of measures are used to compare the words",
+          "items": {
+            "enum": ["relatedness", "similarity"],
+            "type": "string"
+          },
+          "type": "array"
+        },
+        "name": {
+          "description": "The name of the dataset",
+          "type": "string"
+        },
+        "papers": {
+          "description": "Information about the scientific papers describing the dataset",
+          "items": {
+            "$ref": "https://andrefs.com/schemas/2023/SemMeasures#/definitions/Paper"
+          },
+          "type": "array"
+        },
+        "urls": {
+          "description": "Web sites containing information about the dataset",
+          "items": {
+            "format": "uri",
+            "type": "string"
+          },
+          "type": "array"
+        }
+      },
+      "required": [
+        "date",
+        "description",
+        "downloadUrls",
+        "measureTypes",
+        "name",
+        "papers",
+        "urls"
+      ],
+      "type": "object"
+    },
+    "Paper": {
+      "properties": {
+        "title": {
+          "description": "The title of the paper",
+          "type": "string"
+        },
+        "url": {
+          "description": "The URL where the paper can be found",
+          "format": "uri",
+          "type": "string"
+        }
+      },
+      "required": ["title"],
+      "type": "object"
+    },
+    "Partition": {
+      "properties": {
+        "data": {
+          "description": "The data for the partition",
+          "items": {
+            "$ref": "https://andrefs.com/schemas/2023/SemMeasures#/definitions/PartitionData"
+          },
+          "type": "array"
+        },
+        "id": {
+          "description": "An identifier for the partition",
+          "type": "string"
+        },
+        "measureType": {
+          "description": "Which type of measure is used to compare the words",
+          "enum": ["relatedness", "similarity"],
+          "type": "string"
+        }
+      },
+      "required": ["data", "id", "measureType"],
+      "type": "object"
+    },
+    "PartitionData": {
+      "anyOf": [
+        {
+          "allOf": [
+            {
+              "properties": {
+                "word1": {
+                  "description": "The first word in the pair",
+                  "type": "string"
                 },
-                "url": {
-                    "description": "The URL where the paper can be found",
-                    "format": "uri",
-                    "type": "string"
+                "word2": {
+                  "description": "The second word in the pair",
+                  "type": "string"
                 }
+              },
+              "required": ["word1", "word2"],
+              "type": "object"
             },
-            "required": [
-                "title"
-            ],
-            "type": "object"
+            {
+              "properties": {
+                "value": {
+                  "description": "The averaged numeric value of the semantic measure for the pair",
+                  "type": "number"
+                }
+              },
+              "required": ["value"],
+              "type": "object"
+            }
+          ]
         },
-        "Partition": {
-            "properties": {
-                "data": {
-                    "description": "The data for the partition",
-                    "items": {
-                        "$ref": "https://andrefs.com/schemas/2023/SemMeasures#/definitions/PartitionData"
-                    },
-                    "type": "array"
+        {
+          "allOf": [
+            {
+              "properties": {
+                "word1": {
+                  "description": "The first word in the pair",
+                  "type": "string"
                 },
-                "id": {
-                    "description": "An identifier for the partition",
-                    "type": "string"
-                },
-                "measureType": {
-                    "description": "Which type of measure is used to compare the words",
-                    "enum": [
-                        "relatedness",
-                        "similarity"
-                    ],
-                    "type": "string"
+                "word2": {
+                  "description": "The second word in the pair",
+                  "type": "string"
                 }
+              },
+              "required": ["word1", "word2"],
+              "type": "object"
             },
-            "required": [
-                "data",
-                "id",
-                "measureType"
-            ],
-            "type": "object"
-        },
-        "PartitionData": {
-            "anyOf": [
-                {
-                    "allOf": [
-                        {
-                            "properties": {
-                                "word1": {
-                                    "description": "The first word in the pair",
-                                    "type": "string"
-                                },
-                                "word2": {
-                                    "description": "The second word in the pair",
-                                    "type": "string"
-                                }
-                            },
-                            "required": [
-                                "word1",
-                                "word2"
-                            ],
-                            "type": "object"
-                        },
-                        {
-                            "properties": {
-                                "value": {
-                                    "description": "The averaged numeric value of the semantic measure for the pair",
-                                    "type": "number"
-                                }
-                            },
-                            "required": [
-                                "value"
-                            ],
-                            "type": "object"
-                        }
-                    ]
-                },
-                {
-                    "allOf": [
-                        {
-                            "properties": {
-                                "word1": {
-                                    "description": "The first word in the pair",
-                                    "type": "string"
-                                },
-                                "word2": {
-                                    "description": "The second word in the pair",
-                                    "type": "string"
-                                }
-                            },
-                            "required": [
-                                "word1",
-                                "word2"
-                            ],
-                            "type": "object"
-                        },
-                        {
-                            "properties": {
-                                "values": {
-                                    "description": "The individual numeric values of the semantic measure for the pair",
-                                    "items": {
-                                        "type": "number"
-                                    },
-                                    "type": "array"
-                                }
-                            },
-                            "required": [
-                                "values"
-                            ],
-                            "type": "object"
-                        }
-                    ]
+            {
+              "properties": {
+                "values": {
+                  "description": "The individual numeric values of the semantic measure for the pair",
+                  "items": {
+                    "type": "number"
+                  },
+                  "type": "array"
                 }
-            ]
+              },
+              "required": ["values"],
+              "type": "object"
+            }
+          ]
         }
+      ]
     }
+  }
 }
-
diff --git a/src/lib/experiments/compare-mc30.ts b/src/lib/experiments/compare-mc30.ts
index 89199a6..f08eade 100644
--- a/src/lib/experiments/compare-mc30.ts
+++ b/src/lib/experiments/compare-mc30.ts
@@ -1,152 +1,157 @@
-import mc30 from 'punuy-datasets/mc30';
-import rg65 from 'punuy-datasets/rg65';
-import ws353 from 'punuy-datasets/ws353';
-import pcorrtest from '@stdlib/stats-pcorrtest';
+import mc30 from "punuy-datasets/mc30"
+import rg65 from "punuy-datasets/rg65"
+import ws353 from "punuy-datasets/ws353"
+import pcorrtest from "@stdlib/stats-pcorrtest"
 
-import { Model, ModelIds, gpt35turbo, gpt4, gpt4turbo } from '../models'
-import { JsonSyntaxError } from "../validation";
-import logger from '../logger';
+import { Model, ModelIds, gpt35turbo, gpt4, gpt4turbo } from "../models"
+import { JsonSyntaxError } from "../validation"
+import logger from "../logger"
 
 interface DatasetScores {
   [word1: string]: {
     [word2: string]: {
-      [dataset: string]: number;
+      [dataset: string]: number
     }
   }
 }
 
 type ModelsResults = {
-  [key in ModelIds]: string[];
+  [key in ModelIds]: string[]
 }
 
-
 export const loadDatasetScores = async () => {
-  const pairs: DatasetScores = {};
+  const pairs: DatasetScores = {}
 
   for (const part of mc30.partitions) {
     for (const entry of part.data) {
-      pairs[entry.word1] = pairs[entry.word1] || {};
-      pairs[entry.word1][entry.word2] = pairs[entry.word1][entry.word2] || {};
-      if ('value' in entry) {
-        pairs[entry.word1][entry.word2]['mc30'] = entry.value;
+      pairs[entry.word1] = pairs[entry.word1] || {}
+      pairs[entry.word1][entry.word2] = pairs[entry.word1][entry.word2] || {}
+      if ("value" in entry) {
+        pairs[entry.word1][entry.word2]["mc30"] = entry.value
       } else {
-        pairs[entry.word1][entry.word2]['mc30'] = entry.values.reduce((a, b) => a + b, 0) / entry.values.length;
+        pairs[entry.word1][entry.word2]["mc30"] =
+          entry.values.reduce((a, b) => a + b, 0) / entry.values.length
       }
     }
   }
 
   for (const part of rg65.partitions) {
     for (const entry of part.data) {
-      const value = 'value' in entry ? entry.value : entry.values.reduce((a, b) => a + b, 0) / entry.values.length;
+      const value =
+        "value" in entry
+          ? entry.value
+          : entry.values.reduce((a, b) => a + b, 0) / entry.values.length
 
       if (entry.word1 in pairs && entry.word2 in pairs[entry.word1]) {
-        pairs[entry.word1][entry.word2][rg65.id] = value;
+        pairs[entry.word1][entry.word2][rg65.id] = value
       } else if (entry.word2 in pairs && entry.word1 in pairs[entry.word2]) {
-        pairs[entry.word2][entry.word1][rg65.id] = value;
+        pairs[entry.word2][entry.word1][rg65.id] = value
       }
     }
   }
 
   for (const part of ws353.partitions) {
     for (const entry of part.data) {
-      const value = 'value' in entry ? entry.value : entry.values.reduce((a, b) => a + b, 0) / entry.values.length;
+      const value =
+        "value" in entry
+          ? entry.value
+          : entry.values.reduce((a, b) => a + b, 0) / entry.values.length
 
       if (entry.word1 in pairs && entry.word2 in pairs[entry.word1]) {
-        pairs[entry.word1][entry.word2][ws353.id] = value * (4 / 10);
+        pairs[entry.word1][entry.word2][ws353.id] = value * (4 / 10)
       } else if (entry.word2 in pairs && entry.word1 in pairs[entry.word2]) {
-        pairs[entry.word2][entry.word1][ws353.id] = value * (4 / 10);
+        pairs[entry.word2][entry.word1][ws353.id] = value * (4 / 10)
       }
     }
   }
 
   // chord vs cord
   // see http://dx.doi.org/10.1162/coli.2006.32.1.13
-  delete pairs['chord'];
+  delete pairs["chord"]
 
-  return pairs;
+  return pairs
 }
 
 const getPairs = (scores: DatasetScores) => {
-  const pairs: [string, string][] = [];
+  const pairs: [string, string][] = []
 
   for (const word1 in scores) {
     for (const word2 in scores[word1]) {
-      pairs.push([word1, word2]);
+      pairs.push([word1, word2])
     }
   }
 
-  return pairs;
+  return pairs
 }
 
-
-const name = 'compare-mc30';
-const description = 'Compare the scores of multiple AI models with the scores from multiple human annotations of the MC30 pair set.';
+const name = "compare-mc30"
+const description =
+  "Compare the scores of multiple AI models with the scores from multiple human annotations of the MC30 pair set."
 const genPrompt = (pairs: string[][]) =>
   'Please rate the similarity of the following pairs of words on a scale of 0 to 4, where 0 means "completely unrelated" and 4 means "very similar". Fractional values are allowed.\n\n' +
-  pairs.map(([w1, w2]) => `${w1} ${w2}`).join('\n');
-
-
+  pairs.map(([w1, w2]) => `${w1} ${w2}`).join("\n")
 
 // TODO fix when OpenAI supports items with tuple definition in JSON schema
 // https://community.openai.com/t/json-schema-tuple-validation-support/273554
 const resultSchema = {
-  "type": "object",
-  "properties": {
-    "scores": {
-      "type": "array",
-      "items": {
-        "type": "object",
-        "properties": {
-          "words": { "type": "array", "items": { "type": "string" } },
-          "score": { "type": "number" }
-        }
-      }
-    }
-  }
+  type: "object",
+  properties: {
+    scores: {
+      type: "array",
+      items: {
+        type: "object",
+        properties: {
+          words: { type: "array", items: { type: "string" } },
+          score: { type: "number" },
+        },
+      },
+    },
+  },
 }
 
 async function runTrialModel(model: Model, prompt: string) {
   const f = {
-    name: 'evaluate_scores',
-    description: 'Evaluate the word similarity scores.',
-    parameters: resultSchema
-  };
+    name: "evaluate_scores",
+    description: "Evaluate the word similarity scores.",
+    parameters: resultSchema,
+  }
 
-  const res = await model.makeRequest(prompt, { function: f });
-  return res;
+  const res = await model.makeRequest(prompt, { function: f })
+  return res
 }
 
 async function runTrialsModel(trials: number, model: Model, prompt: string) {
-  logger.info(`  model ${model.modelId}.`);
-  logger.debug(`Prompt: ${prompt}`);
-  const results = [];
+  logger.info(`  model ${model.modelId}.`)
+  logger.debug(`Prompt: ${prompt}`)
+  const results = []
   for (let i = 0; i < trials; i++) {
     logger.info(`    trial #${i + 1} of ${trials}`)
-    const res = await runTrialModel(model, prompt);
-    results.push(res.type === 'openai' ? res.data.choices[0].message.tool_calls?.[0].function.arguments || '' : '');
+    const res = await runTrialModel(model, prompt)
+    results.push(
+      res.type === "openai"
+        ? res.data.choices[0].message.tool_calls?.[0].function.arguments || ""
+        : "",
+    )
   }
-  return results;
+  return results
 }
 
 async function runTrials(trials: number) {
-  const scores = await loadDatasetScores();
-  const pairs = getPairs(scores);
-  const prompt = genPrompt(pairs);
-
-  const models = [gpt35turbo, gpt4, gpt4turbo];
-  logger.info(`Running experiment ${name} ${trials} times.`);
+  const scores = await loadDatasetScores()
+  const pairs = getPairs(scores)
+  const prompt = genPrompt(pairs)
 
-  const gpt35turbo_res = await runTrialsModel(trials, gpt35turbo, prompt);
-  const gpt4_res = await runTrialsModel(trials, gpt4, prompt);
-  const gpt4turbo_res = await runTrialsModel(trials, gpt4turbo, prompt);
+  logger.info(`Running experiment ${name} ${trials} times.`)
 
+  const gpt35turbo_res = await runTrialsModel(trials, gpt35turbo, prompt)
+  const gpt4_res = await runTrialsModel(trials, gpt4, prompt)
+  const gpt4turbo_res = await runTrialsModel(trials, gpt4turbo, prompt)
 
   return {
     gpt35turbo: gpt35turbo_res,
     gpt4: gpt4_res,
-    gpt4turbo: gpt4turbo_res
+    gpt4turbo: gpt4turbo_res,
   }
-
 }
 
 interface MC30Results {
@@ -154,18 +159,17 @@ interface MC30Results {
     [word2: string]: {
       models: {
         [model: string]: {
-          avg: number;
-          values: number[];
-          sum: number;
-          count: number;
+          avg: number
+          values: number[]
+          sum: number
+          count: number
         }
-      },
+      }
       human: {
-        [dataset: string]: number;
+        [dataset: string]: number
       }
     }
   }
-
 }
 
 function unzipResults(results: MC30Results) {
@@ -175,136 +179,141 @@ function unzipResults(results: MC30Results) {
     gpt4turbo: [] as number[],
     mc30: [] as number[],
     rg65: [] as number[],
-    ws353: [] as number[]
-  };
+    ws353: [] as number[],
+  }
 
   for (const w1 in results) {
     for (const w2 in results[w1]) {
-      res.gpt35turbo.push(results[w1][w2].models.gpt35turbo.avg);
-      res.gpt4.push(results[w1][w2].models.gpt4.avg);
-      res.gpt4turbo.push(results[w1][w2].models.gpt4turbo.avg);
-      res.mc30.push(results[w1][w2].human.mc30);
-      res.rg65.push(results[w1][w2].human.rg65);
-      res.ws353.push(results[w1][w2].human.ws353);
+      res.gpt35turbo.push(results[w1][w2].models.gpt35turbo.avg)
+      res.gpt4.push(results[w1][w2].models.gpt4.avg)
+      res.gpt4turbo.push(results[w1][w2].models.gpt4turbo.avg)
+      res.mc30.push(results[w1][w2].human.mc30)
+      res.rg65.push(results[w1][w2].human.rg65)
+      res.ws353.push(results[w1][w2].human.ws353)
     }
   }
 
-  return res;
+  return res
 }
 
-
 async function validate(modelsRes: ModelsResults, humanScores: DatasetScores) {
   try {
-    let res = mergeResults(modelsRes, humanScores);
-    let arrays = unzipResults(res);
-    let corrMat = calcCorrelation(Object.values(arrays));
+    const res = mergeResults(modelsRes, humanScores)
+    const arrays = unzipResults(res)
+    const corrMat = calcCorrelation(Object.values(arrays))
 
-    printMatrix(Object.keys(arrays), corrMat);
+    printMatrix(Object.keys(arrays), corrMat)
   } catch (e) {
-    return new JsonSyntaxError();
+    return new JsonSyntaxError()
   }
 }
 
-function printMatrix(varNames: string[], matrix: ReturnType<typeof pcorrtest>[][]) {
+function printMatrix(
+  varNames: string[],
+  matrix: ReturnType<typeof pcorrtest>[][],
+) {
   for (let i = 0; i < varNames.length - 1; i++) {
     for (let j = i + 1; j < varNames.length; j++) {
-      let r = matrix[i][j];
-      console.log(`----------------------\n${varNames[i]} vs ${varNames[j]}`);
-      console.log(r.print());
+      const r = matrix[i][j]
+      console.log(`----------------------\n${varNames[i]} vs ${varNames[j]}`)
+      console.log(r.print())
     }
   }
 
-  console.log('\n\n,' + varNames.join(','));
+  console.log("\n\n," + varNames.join(","))
   for (let i = 0; i < varNames.length; i++) {
-    console.log([varNames[i], ...matrix[i].map((r) => r?.pcorr.toFixed(2))].join(','));
+    console.log(
+      [varNames[i], ...matrix[i].map(r => r?.pcorr.toFixed(2))].join(","),
+    )
   }
-  console.log('\n\n');
+  console.log("\n\n")
 }
 
-
 function calcCorrelation(data: number[][]) {
-  const corrMatrix = [] as ReturnType<typeof pcorrtest>[][];
+  const corrMatrix = [] as ReturnType<typeof pcorrtest>[][]
 
   for (let i = 0; i < data.length; i++) {
-    corrMatrix[i] = [];
+    corrMatrix[i] = []
     for (let j = 0; j < data.length; j++) {
       if (i < j) {
-        const corr = pcorrtest(data[i], data[j]);
-        corrMatrix[i][j] = corr;
+        const corr = pcorrtest(data[i], data[j])
+        corrMatrix[i][j] = corr
       }
     }
   }
-  return corrMatrix;
-
+  return corrMatrix
 }
 
 function mergeResults(modelsRes: ModelsResults, humanScores: DatasetScores) {
-  let res = {} as MC30Results;
+  const res = {} as MC30Results
 
   try {
-    const gpt35turbo = modelsRes.gpt35turbo.map((r) => JSON.parse(r)); // TODO cast to resultSchema somehow
-    const gpt4 = modelsRes.gpt4.map((r) => JSON.parse(r));
-    const gpt4turbo = modelsRes.gpt4turbo.map((r) => JSON.parse(r));
+    const gpt35turbo = modelsRes.gpt35turbo.map(r => JSON.parse(r)) // TODO cast to resultSchema somehow
+    const gpt4 = modelsRes.gpt4.map(r => JSON.parse(r))
+    const gpt4turbo = modelsRes.gpt4turbo.map(r => JSON.parse(r))
 
-    let modelName = 'gpt35turbo';
+    let modelName = "gpt35turbo"
     for (const score of gpt35turbo.flatMap(({ scores }) => [...scores])) {
-      const [w1, w2] = score.words;
-      res[w1] = res[w1] || {};
-      res[w1][w2] = res[w1][w2] || { human: {}, models: {} };
-      res[w1][w2].models[modelName] = res[w1][w2].models[modelName] || { values: [] };
-      res[w1][w2].models[modelName].values.push(score.score);
+      const [w1, w2] = score.words
+      res[w1] = res[w1] || {}
+      res[w1][w2] = res[w1][w2] || { human: {}, models: {} }
+      res[w1][w2].models[modelName] = res[w1][w2].models[modelName] || {
+        values: [],
+      }
+      res[w1][w2].models[modelName].values.push(score.score)
     }
     for (const w1 in res) {
       for (const w2 in res[w1]) {
-        res[w1][w2].models[modelName].avg = res[w1][w2]
-          .models[modelName]
-          .values
-          .reduce((a, b) => a + b, 0) / res[w1][w2].models[modelName].values.length;
+        res[w1][w2].models[modelName].avg =
+          res[w1][w2].models[modelName].values.reduce((a, b) => a + b, 0) /
+          res[w1][w2].models[modelName].values.length
       }
     }
 
-    modelName = 'gpt4';
+    modelName = "gpt4"
     for (const score of gpt4.flatMap(({ scores }) => [...scores])) {
-      const [w1, w2] = score.words;
-      res[w1] = res[w1] || {};
-      res[w1][w2] = res[w1][w2] || { human: {}, models: {} };
-      res[w1][w2].models[modelName] = res[w1][w2].models[modelName] || { values: [] };
-      res[w1][w2].models[modelName].values.push(score.score);
+      const [w1, w2] = score.words
+      res[w1] = res[w1] || {}
+      res[w1][w2] = res[w1][w2] || { human: {}, models: {} }
+      res[w1][w2].models[modelName] = res[w1][w2].models[modelName] || {
+        values: [],
+      }
+      res[w1][w2].models[modelName].values.push(score.score)
     }
     for (const w1 in res) {
       for (const w2 in res[w1]) {
-        res[w1][w2].models[modelName].avg = res[w1][w2]
-          .models[modelName]
-          .values
-          .reduce((a, b) => a + b, 0) / res[w1][w2].models[modelName].values.length;
+        res[w1][w2].models[modelName].avg =
+          res[w1][w2].models[modelName].values.reduce((a, b) => a + b, 0) /
+          res[w1][w2].models[modelName].values.length
       }
     }
 
-    modelName = 'gpt4turbo';
+    modelName = "gpt4turbo"
     for (const score of gpt4turbo.flatMap(({ scores }) => [...scores])) {
-      const [w1, w2] = score.words;
-      res[w1] = res[w1] || {};
-      res[w1][w2] = res[w1][w2] || { human: {}, models: {} };
-      res[w1][w2].models[modelName] = res[w1][w2].models[modelName] || { values: [] };
-      res[w1][w2].models[modelName].values.push(score.score);
+      const [w1, w2] = score.words
+      res[w1] = res[w1] || {}
+      res[w1][w2] = res[w1][w2] || { human: {}, models: {} }
+      res[w1][w2].models[modelName] = res[w1][w2].models[modelName] || {
+        values: [],
+      }
+      res[w1][w2].models[modelName].values.push(score.score)
     }
     for (const w1 in res) {
       for (const w2 in res[w1]) {
-        res[w1][w2].models[modelName].avg = res[w1][w2]
-          .models[modelName]
-          .values
-          .reduce((a, b) => a + b, 0) / res[w1][w2].models[modelName].values.length;
+        res[w1][w2].models[modelName].avg =
+          res[w1][w2].models[modelName].values.reduce((a, b) => a + b, 0) /
+          res[w1][w2].models[modelName].values.length
       }
     }
 
     for (const w1 in humanScores) {
       for (const w2 in humanScores[w1]) {
-        res[w1][w2].human = humanScores[w1][w2];
+        res[w1][w2].human = humanScores[w1][w2]
       }
     }
-    return res;
+    return res
   } catch (e) {
-    throw new JsonSyntaxError();
+    throw new JsonSyntaxError()
   }
 }
 
@@ -314,7 +323,7 @@ const CompareMC30Experiment = {
   genPrompt,
   schema: resultSchema,
   runTrials,
-  validate
+  validate,
 }
 
-export default CompareMC30Experiment;
+export default CompareMC30Experiment
diff --git a/src/lib/experiments/experiment.ts b/src/lib/experiments/experiment.ts
index 0fb85c3..ad7b49c 100644
--- a/src/lib/experiments/experiment.ts
+++ b/src/lib/experiments/experiment.ts
@@ -1,55 +1,110 @@
-import OpenAI from "openai";
-import { Model } from "../models";
-import { DatasetProfile } from "../types";
-import { ValidationResult, ValidationType, combineValidations } from "../validation";
-import logger from "../logger";
-import fs from 'fs/promises';
-import oldFs from 'fs';
-
+import OpenAI from "openai"
+import { Model } from "../models"
+import { DatasetProfile } from "../types"
+import {
+  ValidationResult,
+  ValidationType,
+  combineValidations,
+} from "../validation"
+import logger from "../logger"
+import fs from "fs/promises"
+import oldFs from "fs"
 
 class Experiment {
-  name: string;
-  description: string;
-  genPrompt: (ds: DatasetProfile) => string;
-  schema: any; // TODO
-  runTrials: (this: Experiment, trials: number, ds: DatasetProfile, model: Model) => Promise<string[]>;
-  validateTrial: (ds: DatasetProfile, data: string) => Promise<ValidationResult>;
-  validate: (ds: DatasetProfile, data: string[]) => Promise<{ trialResults: ValidationResult[], combinedResult: AggregatedValidationResult }>;
-  perform: (this: Experiment, trials: number, ds: DatasetProfile, model: Model, traceId?: number) => Promise<ExperimentData>;
+  name: string
+  description: string
+  genPrompt: (ds: DatasetProfile) => string
+  schema: any // TODO
+  runTrials: (
+    this: Experiment,
+    trials: number,
+    ds: DatasetProfile,
+    model: Model,
+  ) => Promise<string[]>
+  validateTrial: (ds: DatasetProfile, data: string) => Promise<ValidationResult>
+  validate: (
+    ds: DatasetProfile,
+    data: string[],
+  ) => Promise<{
+    trialResults: ValidationResult[]
+    combinedResult: AggregatedValidationResult
+  }>
+  perform: (
+    this: Experiment,
+    trials: number,
+    ds: DatasetProfile,
+    model: Model,
+    traceId?: number,
+  ) => Promise<ExperimentData>
 
   constructor(
     name: string,
     description: string,
     genPrompt: (ds: DatasetProfile) => string,
     schema: any,
-    runTrial: (prompt: string, schema: any, ds: DatasetProfile, model: Model) => Promise<TrialResult>,
-    validateTrial: (ds: DatasetProfile, data: string) => Promise<ValidationResult>,
+    runTrial: (
+      prompt: string,
+      schema: any,
+      ds: DatasetProfile,
+      model: Model,
+    ) => Promise<TrialResult>,
+    validateTrial: (
+      ds: DatasetProfile,
+      data: string,
+    ) => Promise<ValidationResult>,
   ) {
-    this.name = name;
-    this.description = description;
-    this.genPrompt = genPrompt;
-    this.schema = schema;
-    this.runTrials = async function(this: Experiment, trials: number, ds: DatasetProfile, model: Model) {
-      const prompt = this.genPrompt(ds);
-      logger.info(`Running experiment ${this.name} ${trials} times on model ${model.modelId}.`);
-      logger.debug(`Prompt: ${prompt}`);
-
-      const results = [];
+    this.name = name
+    this.description = description
+    this.genPrompt = genPrompt
+    this.schema = schema
+    this.runTrials = async function (
+      this: Experiment,
+      trials: number,
+      ds: DatasetProfile,
+      model: Model,
+    ) {
+      const prompt = this.genPrompt(ds)
+      logger.info(
+        `Running experiment ${this.name} ${trials} times on model ${model.modelId}.`,
+      )
+      logger.debug(`Prompt: ${prompt}`)
+
+      const results = []
       for (let i = 0; i < trials; i++) {
         logger.info(`  trial #${i + 1} of ${trials}`)
-        const res = await runTrial(prompt, this.schema, ds, model);
-        results.push(res.type === 'openai' ? res.data.choices[0].message.tool_calls?.[0].function.arguments || '' : '');
+        const res = await runTrial(prompt, this.schema, ds, model)
+        results.push(
+          res.type === "openai"
+            ? res.data.choices[0].message.tool_calls?.[0].function.arguments ||
+                ""
+            : "",
+        )
+      }
+      return results
+    }
+    this.validateTrial = validateTrial
+    this.validate = async function (
+      this: Experiment,
+      ds: DatasetProfile,
+      data: string[],
+    ) {
+      const trialResults = await Promise.all(
+        data.map(d => this.validateTrial(ds, d)),
+      )
+      return {
+        trialResults,
+        combinedResult: await combineValidations(trialResults),
       }
-      return results;
     }
-    this.validateTrial = validateTrial;
-    this.validate = async function(this: Experiment, ds: DatasetProfile, data: string[]) {
-      const trialResults = await Promise.all(data.map((d) => this.validateTrial(ds, d)));
-      return { trialResults, combinedResult: await combineValidations(trialResults) };
-    };
-    this.perform = async function(this: Experiment, trials: number, ds: DatasetProfile, model: Model, traceId?: number): Promise<ExperimentData> {
-      const results = await this.runTrials(trials, ds, model);
-      const { trialResults, combinedResult } = await this.validate(ds, results);
+    this.perform = async function (
+      this: Experiment,
+      trials: number,
+      ds: DatasetProfile,
+      model: Model,
+      traceId?: number,
+    ): Promise<ExperimentData> {
+      const results = await this.runTrials(trials, ds, model)
+      const { trialResults, combinedResult } = await this.validate(ds, results)
 
       const expData = {
         name: this.name,
@@ -59,56 +114,56 @@ class Experiment {
         dsId: ds.id,
         modelId: model.modelId,
         trialResults,
-        combinedResult
-      };
+        combinedResult,
+      }
 
-      await saveExperimentData(expData);
-      return expData;
+      await saveExperimentData(expData)
+      return expData
     }
   }
 }
 
 export async function saveExperimentData(data: ExperimentData) {
-  const ts = data.traceId;
-  const dsId = data.dsId;
-  const expName = data.name;
-  const modelId = data.modelId;
-  const rootFolder = './results';
-  const filename = `${rootFolder}/${ts}_${expName}_${dsId}_${modelId}.json`;
-  const json = JSON.stringify(data, null, 2);
-
-  logger.info(`Saving experiment ${data.name} ${data.trialResults.length} times on model ${data.modelId} to ${filename}.`);
+  const ts = data.traceId
+  const dsId = data.dsId
+  const expName = data.name
+  const modelId = data.modelId
+  const rootFolder = "./results"
+  const filename = `${rootFolder}/${ts}_${expName}_${dsId}_${modelId}.json`
+  const json = JSON.stringify(data, null, 2)
+
+  logger.info(
+    `Saving experiment ${data.name} ${data.trialResults.length} times on model ${data.modelId} to ${filename}.`,
+  )
 
   if (!oldFs.existsSync(rootFolder)) {
-    await fs.mkdir(rootFolder);
+    await fs.mkdir(rootFolder)
   }
 
-  await fs.writeFile(filename, json);
+  await fs.writeFile(filename, json)
 }
 
 export interface ExperimentData {
-  name: string;
-  traceId: number;
+  name: string
+  traceId: number
   prompt: string
-  schema: any;
-  dsId: string;
-  modelId: string;
-  trialResults: ValidationResult[],
-  combinedResult: AggregatedValidationResult,
+  schema: any
+  dsId: string
+  modelId: string
+  trialResults: ValidationResult[]
+  combinedResult: AggregatedValidationResult
 }
 
 export interface AggregatedValidationResult {
-  avg: number;
+  avg: number
   resultTypes: {
-    [key in ValidationType]: number;
+    [key in ValidationType]: number
   }
 }
 
 export type TrialResult = {
-  type: 'openai';
-  data: OpenAI.Chat.Completions.ChatCompletion;
+  type: "openai"
+  data: OpenAI.Chat.Completions.ChatCompletion
 }
 
-export default Experiment;
-
-
+export default Experiment
diff --git a/src/lib/experiments/index.ts b/src/lib/experiments/index.ts
index 0b82231..21c09c9 100644
--- a/src/lib/experiments/index.ts
+++ b/src/lib/experiments/index.ts
@@ -1,19 +1,16 @@
-import dsSampleFromDsName from "./prior-knowledge/dsSampleFromDsName";
-export { dsSampleFromDsName };
+import dsSampleFromDsName from "./prior-knowledge/dsSampleFromDsName"
+export { dsSampleFromDsName }
 
-import dsPaperFromDsName from "./prior-knowledge/dsPaperFromDsName";
-export { dsPaperFromDsName };
+import dsPaperFromDsName from "./prior-knowledge/dsPaperFromDsName"
+export { dsPaperFromDsName }
 
-import dsSampleFromDsSample from "./prior-knowledge/dsSampleFromDsSample";
-export { dsSampleFromDsSample };
-
-import dsNameFromDsSample from "./prior-knowledge/dsNameFromDsSample";
-export { dsNameFromDsSample };
-
-import compareMc30 from "./compare-mc30";
-export { compareMc30 };
-
-export * from "./experiment";
+import dsSampleFromDsSample from "./prior-knowledge/dsSampleFromDsSample"
+export { dsSampleFromDsSample }
 
+import dsNameFromDsSample from "./prior-knowledge/dsNameFromDsSample"
+export { dsNameFromDsSample }
 
+import compareMc30 from "./compare-mc30"
+export { compareMc30 }
 
+export * from "./experiment"
diff --git a/src/lib/experiments/prior-knowledge/dsNameFromDsSample.ts b/src/lib/experiments/prior-knowledge/dsNameFromDsSample.ts
index 3f13c51..212533b 100644
--- a/src/lib/experiments/prior-knowledge/dsNameFromDsSample.ts
+++ b/src/lib/experiments/prior-knowledge/dsNameFromDsSample.ts
@@ -1,66 +1,81 @@
-import Experiment from "../experiment";
-import { Model } from "../../models";
-import { DatasetProfile } from "../../types";
-import { DataCorrect, DataIncomplete, DataIncorrect, DataPartiallyIncorrect, JsonSyntaxError, NoData, ValidationResult, ValidationType, combineValidations } from "../../validation";
+import Experiment from "../experiment"
+import { Model } from "../../models"
+import { DatasetProfile } from "../../types"
+import {
+  DataCorrect,
+  DataIncomplete,
+  DataIncorrect,
+  DataPartiallyIncorrect,
+  JsonSyntaxError,
+  NoData,
+  ValidationResult,
+  ValidationType,
+  combineValidations,
+} from "../../validation"
 
-
-const name = 'ds-name-from-ds-sample';
-const description = 'Check if LLM knows a dataset by giving it 10 pairs and asking for 5 more.';
+const name = "ds-name-from-ds-sample"
+const description =
+  "Check if LLM knows a dataset by giving it 10 pairs and asking for 5 more."
 const genPrompt = (ds: DatasetProfile) => {
-  return `Which semantic measures evaluation dataset do these pairs of concepts belong to?\n` +
-    ds.partitions[0].data.slice(0, 10).map(({ word1, word2 }) => `${word1} ${word2}`).join('\n');
+  return (
+    `Which semantic measures evaluation dataset do these pairs of concepts belong to?\n` +
+    ds.partitions[0].data
+      .slice(0, 10)
+      .map(({ word1, word2 }) => `${word1} ${word2}`)
+      .join("\n")
+  )
 }
 const resultSchema = {
-  "type": "object",
-  "properties": {
-    "name": {
-      "type": "string",
+  type: "object",
+  properties: {
+    name: {
+      type: "string",
     },
-    "year": {
-      "type": "string",
+    year: {
+      type: "string",
     },
-    "authors": {
-      "type": "array",
-      "items": {
-        type: 'string'
-      }
-    }
-  }
+    authors: {
+      type: "array",
+      items: {
+        type: "string",
+      },
+    },
+  },
 }
 
-async function runTrial(prompt: string, schema: any, _: DatasetProfile, model: Model) {
+async function runTrial(
+  prompt: string,
+  schema: any,
+  _: DatasetProfile,
+  model: Model,
+) {
   const f = {
-    name: 'validate_dataset',
-    description: 'Validates the dataset information.',
-    parameters: schema
-  };
+    name: "validate_dataset",
+    description: "Validates the dataset information.",
+    parameters: schema,
+  }
 
-  const result = await model.makeRequest(prompt, { function: f });
-  return result;
+  const result = await model.makeRequest(prompt, { function: f })
+  return result
 }
 
-
 async function validateTrial(ds: DatasetProfile, data: string) {
-  if (!data.trim()) { return new NoData(); }
+  if (!data.trim()) {
+    return new NoData()
+  }
   try {
-    const got = JSON.parse(data);
-    return new DataCorrect(got);
+    const got = JSON.parse(data)
+    return new DataCorrect(got)
   } catch (e) {
-    return new JsonSyntaxError(data);
+    return new JsonSyntaxError(data)
   }
 }
 
-
-
-
 export default new Experiment(
   name,
   description,
   genPrompt,
   resultSchema,
   runTrial,
-  validateTrial
-);
-
-
-
+  validateTrial,
+)
diff --git a/src/lib/experiments/prior-knowledge/dsPaperFromDsName.ts b/src/lib/experiments/prior-knowledge/dsPaperFromDsName.ts
index a6be6a2..5c3c8ba 100644
--- a/src/lib/experiments/prior-knowledge/dsPaperFromDsName.ts
+++ b/src/lib/experiments/prior-knowledge/dsPaperFromDsName.ts
@@ -1,71 +1,89 @@
-import Experiment, { TrialResult } from "../experiment";
-import { Model } from "../../models";
-import { DatasetProfile } from "../../types";
-import { DataCorrect, DataIncomplete, DataIncorrect, DataPartiallyIncorrect, JsonSchemaError, JsonSyntaxError, NoData } from "../../validation";
-import { distance } from 'fastest-levenshtein';
+import Experiment, { TrialResult } from "../experiment"
+import { Model } from "../../models"
+import { DatasetProfile } from "../../types"
+import {
+  DataCorrect,
+  DataIncomplete,
+  DataIncorrect,
+  DataPartiallyIncorrect,
+  JsonSchemaError,
+  JsonSyntaxError,
+  NoData,
+} from "../../validation"
+import { distance } from "fastest-levenshtein"
 import Ajv, { JSONSchemaType } from "ajv"
 const ajv = new Ajv()
 
-
-const name = 'ds-paper-from-ds-name';
-const description = 'Check if LLM can, when given a dataset name, identify the scientific paper describing it';
+const name = "ds-paper-from-ds-name"
+const description =
+  "Check if LLM can, when given a dataset name, identify the scientific paper describing it"
 const genPrompt = (ds: DatasetProfile) => {
-  const year = ds.metadata.date.split('-')[0];
+  const year = ds.metadata.date.split("-")[0]
   return `${ds.metadata.name} is a semantic measure gold standard dataset, published in ${year}. Please return the title of the scientific article describing this dataset.`
 }
 const resultSchema = {
-  "type": "object",
-  "properties": {
-    "title": {
-      "type": "string",
-    }
-  }
+  type: "object",
+  properties: {
+    title: {
+      type: "string",
+    },
+  },
 }
-type ResultSchema = JSONSchemaType<typeof resultSchema>;
+type ResultSchema = JSONSchemaType<typeof resultSchema>
 
-const validateSchema = ajv.compile<ResultSchema>(resultSchema);
+const validateSchema = ajv.compile<ResultSchema>(resultSchema)
 
-async function runTrial(prompt: string, schema: any, _: DatasetProfile, model: Model) {
+async function runTrial(
+  prompt: string,
+  schema: any,
+  _: DatasetProfile,
+  model: Model,
+) {
   const f = {
-    name: 'return-paper-name',
-    description: 'Return the title of the scientific article describing this dataset',
-    parameters: schema
+    name: "return-paper-name",
+    description:
+      "Return the title of the scientific article describing this dataset",
+    parameters: schema,
   }
-  const result = await model.makeRequest(prompt, { function: f });
-  return result;
+  const result = await model.makeRequest(prompt, { function: f })
+  return result
 }
 
-
 async function validateTrial(ds: DatasetProfile, data: string) {
-  if (!data.trim()) { return new NoData(); }
+  if (!data.trim()) {
+    return new NoData()
+  }
 
   try {
-    const got = JSON.parse(data);
+    const got = JSON.parse(data)
     if (!validateSchema(got)) {
-      return new JsonSchemaError(data);
+      return new JsonSchemaError(data)
     }
-    const expected = ds.metadata.papers.map(p => ({ title: p.title }));
+    const expected = ds.metadata.papers.map(p => ({ title: p.title }))
 
-    let bestScore = 1;
-    let bestIndex = -1;
+    let bestScore = 1
+    let bestIndex = -1
 
     for (const [i, exp] of expected.entries()) {
-      const e = exp.title.toLowerCase().trim();
-      const g = got.title.toLowerCase().trim();
-      const d = distance(e, g) / ((e.length + g.length) / 2);
+      const e = exp.title.toLowerCase().trim()
+      const g = got.title.toLowerCase().trim()
+      const d = distance(e, g) / ((e.length + g.length) / 2)
       if (d < bestScore) {
-        bestScore = d;
-        bestIndex = i;
+        bestScore = d
+        bestIndex = i
       }
     }
 
-    const threshold = 0.2;
+    const threshold = 0.2
     if (bestScore < threshold) {
-      return new DataCorrect(got.title);
+      return new DataCorrect(got.title)
     }
-    return new DataIncorrect({ got: got.title, expected: expected.map(e => e.title) });
+    return new DataIncorrect({
+      got: got.title,
+      expected: expected.map(e => e.title),
+    })
   } catch (e) {
-    return new JsonSyntaxError(data);
+    return new JsonSyntaxError(data)
   }
 }
 
@@ -75,8 +93,5 @@ export default new Experiment(
   genPrompt,
   resultSchema,
   runTrial,
-  validateTrial
-);
-
-
-
+  validateTrial,
+)
diff --git a/src/lib/experiments/prior-knowledge/dsSampleFromDsName.test.ts b/src/lib/experiments/prior-knowledge/dsSampleFromDsName.test.ts
index cfcf1c2..1055c84 100644
--- a/src/lib/experiments/prior-knowledge/dsSampleFromDsName.test.ts
+++ b/src/lib/experiments/prior-knowledge/dsSampleFromDsName.test.ts
@@ -1,151 +1,160 @@
-
-import { describe, expect, test } from '@jest/globals';
-import dsSampleFromDsName from './dsSampleFromDsName';
-import { Model } from '../../models/model';
-import { DatasetProfile } from '../../types';
+import { describe, expect, test } from "@jest/globals"
+import dsSampleFromDsName from "./dsSampleFromDsName"
+import { Model } from "../../models/model"
+import { DatasetProfile } from "../../types"
 
 const createMockDataset = () => ({
-  id: 'test',
+  id: "test",
   metadata: {
-    name: 'Dataset Name',
-    description: 'test',
+    name: "Dataset Name",
+    description: "test",
     papers: [],
     urls: [],
-    date: '2021-01-01',
+    date: "2021-01-01",
     downloadUrls: [],
     measureTypes: [],
   },
   partitions: [
     {
-      id: 'test',
-      measureType: 'similarity' as const,
+      id: "test",
+      measureType: "similarity" as const,
       data: [
         {
-          word1: 'test',
-          word2: 'test',
+          word1: "test",
+          word2: "test",
           value: 0.5,
           values: [0.5],
         },
       ],
     },
   ],
-});
-
-const createMockModel = (result: string) => new Model('test', jest.fn(() => Promise.resolve({
-  type: 'openai', data: {
-    id: 'test',
-    model: 'test',
-    object: 'chat.completion',
-    created: 0,
-    choices: [{
-      finish_reason: 'function_call',
-      index: 0,
-      message: {
-        content: null,
-        role: 'assistant',
-        tool_calls: [{
-          id: 'test',
-          type: 'function',
-          function: {
-            name: 'test',
-            arguments: result
-          }
-        }]
-      }
-    }]
-  }
-})));
-
-
-describe('dsSampleFromDsName', () => {
-  describe('genPrompt', () => {
-    test('should generate a prompt', () => {
-      const ds: DatasetProfile = createMockDataset();
-
-      const prompt = dsSampleFromDsName.genPrompt(ds);
-      expect(prompt).toEqual(expect.stringContaining('Dataset Name'));
-      expect(prompt).toEqual(expect.stringContaining('2021'));
-    });
-  });
-
-  describe('run', () => {
-    test('should call model.makeRequest', async () => {
-      const ds: DatasetProfile = createMockDataset();
-
-      const model = createMockModel('this is the result');
-
-      await dsSampleFromDsName.runTrials(2, ds, model);
-      expect(model.makeRequest).toHaveBeenCalledTimes(2);
-    });
-
-    test('should return model.makeRequest result', async () => {
-      const ds: DatasetProfile = createMockDataset();
-
-      const model = createMockModel('this is the result');
-
-      const result = await dsSampleFromDsName.runTrials(2, ds, model);
-      expect(result.length).toEqual(2);
-      expect(result[0]).toEqual('this is the result');
-      expect(result[1]).toEqual('this is the result');
-    });
-
-
-    test('should return empty string if model.makeRequest returns no data', async () => {
-      const ds: DatasetProfile = createMockDataset();
-
-      const model = createMockModel('');
-
-      const result = await dsSampleFromDsName.runTrials(1, ds, model);
-      expect(model.makeRequest).toHaveBeenCalled();
-      expect(result.length).toEqual(1);
-      expect(result[0]).toEqual('');
-    });
-
-  });
-
-  describe('validateTrial', () => {
-    test('should return NoData if data is empty', async () => {
-      const ds: DatasetProfile = createMockDataset();
-
-      const result = await dsSampleFromDsName.validateTrial(ds, '');
-      expect(result.type).toEqual('no-data');
-    });
-
-    test('should return DataIncorrect if data is incorrect', async () => {
-      const ds: DatasetProfile = createMockDataset();
-
-      const result = await dsSampleFromDsName.validateTrial(ds,
+})
+
+const createMockModel = (result: string) =>
+  new Model(
+    "test",
+    jest.fn(() =>
+      Promise.resolve({
+        type: "openai",
+        data: {
+          id: "test",
+          model: "test",
+          object: "chat.completion",
+          created: 0,
+          choices: [
+            {
+              finish_reason: "function_call",
+              index: 0,
+              message: {
+                content: null,
+                role: "assistant",
+                tool_calls: [
+                  {
+                    id: "test",
+                    type: "function",
+                    function: {
+                      name: "test",
+                      arguments: result,
+                    },
+                  },
+                ],
+              },
+            },
+          ],
+        },
+      }),
+    ),
+  )
+
+describe("dsSampleFromDsName", () => {
+  describe("genPrompt", () => {
+    test("should generate a prompt", () => {
+      const ds: DatasetProfile = createMockDataset()
+
+      const prompt = dsSampleFromDsName.genPrompt(ds)
+      expect(prompt).toEqual(expect.stringContaining("Dataset Name"))
+      expect(prompt).toEqual(expect.stringContaining("2021"))
+    })
+  })
+
+  describe("run", () => {
+    test("should call model.makeRequest", async () => {
+      const ds: DatasetProfile = createMockDataset()
+
+      const model = createMockModel("this is the result")
+
+      await dsSampleFromDsName.runTrials(2, ds, model)
+      expect(model.makeRequest).toHaveBeenCalledTimes(2)
+    })
+
+    test("should return model.makeRequest result", async () => {
+      const ds: DatasetProfile = createMockDataset()
+
+      const model = createMockModel("this is the result")
+
+      const result = await dsSampleFromDsName.runTrials(2, ds, model)
+      expect(result.length).toEqual(2)
+      expect(result[0]).toEqual("this is the result")
+      expect(result[1]).toEqual("this is the result")
+    })
+
+    test("should return empty string if model.makeRequest returns no data", async () => {
+      const ds: DatasetProfile = createMockDataset()
+
+      const model = createMockModel("")
+
+      const result = await dsSampleFromDsName.runTrials(1, ds, model)
+      expect(model.makeRequest).toHaveBeenCalled()
+      expect(result.length).toEqual(1)
+      expect(result[0]).toEqual("")
+    })
+  })
+
+  describe("validateTrial", () => {
+    test("should return NoData if data is empty", async () => {
+      const ds: DatasetProfile = createMockDataset()
+
+      const result = await dsSampleFromDsName.validateTrial(ds, "")
+      expect(result.type).toEqual("no-data")
+    })
+
+    test("should return DataIncorrect if data is incorrect", async () => {
+      const ds: DatasetProfile = createMockDataset()
+
+      const result = await dsSampleFromDsName.validateTrial(
+        ds,
 
         JSON.stringify({
-          pairs: [
-            ['test', 'test2'],
-          ]
-        })
-      );
-      expect(result.type).toEqual('data-incorrect');
-    });
+          pairs: [["test", "test2"]],
+        }),
+      )
+      expect(result.type).toEqual("data-incorrect")
+    })
 
-    test('should return DataPartiallyIncorrect if data is partially incorrect', async () => {
-      const ds: DatasetProfile = createMockDataset();
+    test("should return DataPartiallyIncorrect if data is partially incorrect", async () => {
+      const ds: DatasetProfile = createMockDataset()
 
-      const result = await dsSampleFromDsName.validateTrial(ds,
+      const result = await dsSampleFromDsName.validateTrial(
+        ds,
 
         JSON.stringify({
           pairs: [
-            ['test', 'test2'],
-            ['test', 'test'],
-          ]
-        })
-      );
-      expect(result.type).toEqual('data-partially-incorrect');
-    });
-
-    test('should return JsonSyntaxError if data is not valid JSON', async () => {
-      const ds: DatasetProfile = createMockDataset();
-
-      const result = await dsSampleFromDsName.validateTrial(ds, 'not valid json');
-      expect(result.type).toEqual('json-syntax-error');
-    });
-  });
-});
-
+            ["test", "test2"],
+            ["test", "test"],
+          ],
+        }),
+      )
+      expect(result.type).toEqual("data-partially-incorrect")
+    })
+
+    test("should return JsonSyntaxError if data is not valid JSON", async () => {
+      const ds: DatasetProfile = createMockDataset()
+
+      const result = await dsSampleFromDsName.validateTrial(
+        ds,
+        "not valid json",
+      )
+      expect(result.type).toEqual("json-syntax-error")
+    })
+  })
+})
diff --git a/src/lib/experiments/prior-knowledge/dsSampleFromDsName.ts b/src/lib/experiments/prior-knowledge/dsSampleFromDsName.ts
index 8c275d9..9ccc1c1 100644
--- a/src/lib/experiments/prior-knowledge/dsSampleFromDsName.ts
+++ b/src/lib/experiments/prior-knowledge/dsSampleFromDsName.ts
@@ -1,90 +1,103 @@
-import Experiment, { TrialResult } from "../experiment";
-import { Model } from "../../models";
-import { DatasetProfile } from "../../types";
-import { DataCorrect, DataIncomplete, DataIncorrect, DataPartiallyIncorrect, JsonSyntaxError, NoData } from "../../validation";
-
-
-const name = 'ds-sample-from-ds-name';
-const description = 'Check if LLM knows a dataset by asking it to list 5 pairs included in the dataset';
+import Experiment, { TrialResult } from "../experiment"
+import { Model } from "../../models"
+import { DatasetProfile } from "../../types"
+import {
+  DataCorrect,
+  DataIncomplete,
+  DataIncorrect,
+  DataPartiallyIncorrect,
+  JsonSyntaxError,
+  NoData,
+} from "../../validation"
+
+const name = "ds-sample-from-ds-name"
+const description =
+  "Check if LLM knows a dataset by asking it to list 5 pairs included in the dataset"
 const genPrompt = (ds: DatasetProfile) => {
-  const year = ds.metadata.date.split('-')[0];
-  const measureTypes = ds.metadata.measureTypes.join(' and ');
-  return `${ds.metadata.name} is a semantic measure gold standard dataset, published in ${year}. ` +
+  const year = ds.metadata.date.split("-")[0]
+  const measureTypes = ds.metadata.measureTypes.join(" and ")
+  return (
+    `${ds.metadata.name} is a semantic measure gold standard dataset, published in ${year}. ` +
     `It is composed of pairs of concepts and their semantic ${measureTypes} score as reported by humans. ` +
     `Please list 5 pairs of concepts sampled from this dataset.`
+  )
 }
 const resultSchema = {
-  "type": "object",
-  "properties": {
-    "pairs": {
-      "type": "array",
-      "items": {
-        "type": "array",
+  type: "object",
+  properties: {
+    pairs: {
+      type: "array",
+      items: {
+        type: "array",
         items: {
-          type: 'string'
-        }
-      }
-    }
-  }
+          type: "string",
+        },
+      },
+    },
+  },
 }
 
-async function runTrial(prompt: string, schema: any, _: DatasetProfile, model: Model) {
+async function runTrial(
+  prompt: string,
+  schema: any,
+  _: DatasetProfile,
+  model: Model,
+) {
   const f = {
-    name: 'validate_sample',
-    description: 'Validates the pairs sampled from the dataset.',
-    parameters: schema
-  };
+    name: "validate_sample",
+    description: "Validates the pairs sampled from the dataset.",
+    parameters: schema,
+  }
 
-  const result = await model.makeRequest(prompt, { function: f });
-  return result;
+  const result = await model.makeRequest(prompt, { function: f })
+  return result
 }
 
-
 async function validateTrial(ds: DatasetProfile, data: string) {
-  if (!data.trim()) { return new NoData(); }
+  if (!data.trim()) {
+    return new NoData()
+  }
   try {
-    const got = JSON.parse(data);
-    const expected: { [word: string]: { [word: string]: boolean } } = {};
+    const got = JSON.parse(data)
+    const expected: { [word: string]: { [word: string]: boolean } } = {}
 
     for (let { word1, word2 } of ds.partitions[0].data) {
-      const w1 = word1.toLowerCase();
-      const w2 = word2.toLowerCase();
+      const w1 = word1.toLowerCase()
+      const w2 = word2.toLowerCase()
 
-      expected[w1] = expected[w1] || {};
-      expected[w1][w2] = true;
-      expected[w2] = expected[w2] || {};
-      expected[w2][w1] = true;
+      expected[w1] = expected[w1] || {}
+      expected[w1][w2] = true
+      expected[w2] = expected[w2] || {}
+      expected[w2][w1] = true
     }
-    let i = 0;
-    let dataIncorrect = false;
+    let i = 0
+    let dataIncorrect = false
     for (let [word1, word2] of got.pairs) {
-      const w1 = word1.toLowerCase();
-      const w2 = word2.toLowerCase();
+      const w1 = word1.toLowerCase()
+      const w2 = word2.toLowerCase()
 
       if (expected[w1]?.[w2] || expected[w2]?.[w1]) {
-        i++;
-        expected[w1][w2] = false;
-        expected[w2][w1] = false;
+        i++
+        expected[w1][w2] = false
+        expected[w2][w1] = false
       } else {
-        dataIncorrect = true;
+        dataIncorrect = true
       }
     }
 
     if (i === 0) {
-      return new DataIncorrect(got);
+      return new DataIncorrect(got)
     }
     if (dataIncorrect) {
-      return new DataPartiallyIncorrect(i / 5, got);
+      return new DataPartiallyIncorrect(i / 5, got)
     }
     if (i < 5) {
-      return new DataIncomplete(i / 5, got);
+      return new DataIncomplete(i / 5, got)
     }
-    return new DataCorrect(got);
-
+    return new DataCorrect(got)
   } catch (e) {
-    return new JsonSyntaxError(data);
+    return new JsonSyntaxError(data)
   }
-
 }
 
 export default new Experiment(
@@ -93,8 +106,5 @@ export default new Experiment(
   genPrompt,
   resultSchema,
   runTrial,
-  validateTrial
-);
-
-
-
+  validateTrial,
+)
diff --git a/src/lib/experiments/prior-knowledge/dsSampleFromDsSample.ts b/src/lib/experiments/prior-knowledge/dsSampleFromDsSample.ts
index 9bf53c3..689520c 100644
--- a/src/lib/experiments/prior-knowledge/dsSampleFromDsSample.ts
+++ b/src/lib/experiments/prior-knowledge/dsSampleFromDsSample.ts
@@ -1,90 +1,106 @@
-import Experiment, { TrialResult } from "../experiment";
-import { Model } from "../../models";
-import { DatasetProfile } from "../../types";
-import { DataCorrect, DataIncomplete, DataIncorrect, DataPartiallyIncorrect, JsonSyntaxError, NoData } from "../../validation";
-
-
-const name = 'ds-sample-from-ds-sample';
-const description = 'Check if LLM knows a dataset by giving it 10 pairs and asking for 5 more.';
+import Experiment, { TrialResult } from "../experiment"
+import { Model } from "../../models"
+import { DatasetProfile } from "../../types"
+import {
+  DataCorrect,
+  DataIncomplete,
+  DataIncorrect,
+  DataPartiallyIncorrect,
+  JsonSyntaxError,
+  NoData,
+} from "../../validation"
+
+const name = "ds-sample-from-ds-sample"
+const description =
+  "Check if LLM knows a dataset by giving it 10 pairs and asking for 5 more."
 const genPrompt = (ds: DatasetProfile) => {
-  const numberOfPairs = ds.partitions.reduce((acc, p) => acc + p.data.length, 0);
-  const measureTypes = ds.metadata.measureTypes.join(' and ');
-  return `A published semantic measure gold standard dataset is composed of ${numberOfPairs} pairs of concepts and their semantic ${measureTypes} score as reported by humans. ` +
+  const numberOfPairs = ds.partitions.reduce((acc, p) => acc + p.data.length, 0)
+  const measureTypes = ds.metadata.measureTypes.join(" and ")
+  return (
+    `A published semantic measure gold standard dataset is composed of ${numberOfPairs} pairs of concepts and their semantic ${measureTypes} score as reported by humans. ` +
     `I only have 10 of the pairs included in the dataset. Please give me a list of 5 other pairs of concepts belonging to the same dataset but not included in my list.\n` +
-    ds.partitions[0].data.slice(0, 10).map(({ word1, word2 }) => `${word1} ${word2}`).join('\n');
+    ds.partitions[0].data
+      .slice(0, 10)
+      .map(({ word1, word2 }) => `${word1} ${word2}`)
+      .join("\n")
+  )
 }
 const resultSchema = {
-  "type": "object",
-  "properties": {
-    "pairs": {
-      "type": "array",
-      "items": {
-        "type": "array",
+  type: "object",
+  properties: {
+    pairs: {
+      type: "array",
+      items: {
+        type: "array",
         items: {
-          type: 'string'
-        }
-      }
-    }
-  }
+          type: "string",
+        },
+      },
+    },
+  },
 }
 
-async function runTrial(prompt: string, schema: any, _: DatasetProfile, model: Model) {
+async function runTrial(
+  prompt: string,
+  schema: any,
+  _: DatasetProfile,
+  model: Model,
+) {
   const f = {
-    name: 'validate_sample',
-    description: 'Validates the pairs sampled from the dataset.',
-    parameters: schema
-  };
+    name: "validate_sample",
+    description: "Validates the pairs sampled from the dataset.",
+    parameters: schema,
+  }
 
-  const result = await model.makeRequest(prompt, { function: f });
-  return result;
+  const result = await model.makeRequest(prompt, { function: f })
+  return result
 }
 
-
 async function validateTrial(ds: DatasetProfile, data: string) {
-  if (!data.trim()) { return new NoData(); }
+  if (!data.trim()) {
+    return new NoData()
+  }
   try {
-    const got = JSON.parse(data);
-    const expected: { [word: string]: { [word: string]: boolean } } = {};
+    const got = JSON.parse(data)
+    const expected: { [word: string]: { [word: string]: boolean } } = {}
 
     for (let { word1, word2 } of ds.partitions[0].data) {
-      const w1 = word1.toLowerCase();
-      const w2 = word2.toLowerCase();
+      const w1 = word1.toLowerCase()
+      const w2 = word2.toLowerCase()
 
-      expected[w1] = expected[w1] || {};
-      expected[w1][w2] = true;
-      expected[w2] = expected[w2] || {};
-      expected[w2][w1] = true;
+      expected[w1] = expected[w1] || {}
+      expected[w1][w2] = true
+      expected[w2] = expected[w2] || {}
+      expected[w2][w1] = true
     }
-    let i = 0;
-    let dataIncorrect = false;
+    let i = 0
+    let dataIncorrect = false
     for (let [word1, word2] of got.pairs) {
-      const w1 = word1.toLowerCase();
-      const w2 = word2.toLowerCase();
+      const w1 = word1.toLowerCase()
+      const w2 = word2.toLowerCase()
 
       if (expected[w1]?.[w2] || expected[w2]?.[w1]) {
-        i++;
-        expected[w1][w2] = false;
-        expected[w2][w1] = false;
+        i++
+        expected[w1][w2] = false
+        expected[w2][w1] = false
       } else {
-        dataIncorrect = true;
+        dataIncorrect = true
       }
     }
 
     if (i === 0) {
-      return new DataIncorrect(got);
+      return new DataIncorrect(got)
     }
     if (dataIncorrect) {
-      return new DataPartiallyIncorrect(i / 5, got);
+      return new DataPartiallyIncorrect(i / 5, got)
     }
     if (i < 5) {
-      return new DataIncomplete(i / 5, got);
+      return new DataIncomplete(i / 5, got)
     }
-    return new DataCorrect(got);
-
+    return new DataCorrect(got)
   } catch (e) {
-    return new JsonSyntaxError(data);
+    return new JsonSyntaxError(data)
   }
-
 }
 
 export default new Experiment(
@@ -93,8 +109,5 @@ export default new Experiment(
   genPrompt,
   resultSchema,
   runTrial,
-  validateTrial
-);
-
-
-
+  validateTrial,
+)
diff --git a/src/lib/logger.ts b/src/lib/logger.ts
index ecd0afb..3e9ee94 100644
--- a/src/lib/logger.ts
+++ b/src/lib/logger.ts
@@ -1,24 +1,25 @@
-import pino from 'pino';
+import pino from "pino"
 
-const level = process.env.PINO_LOG_LEVEL || 'info';
+const level = process.env.PINO_LOG_LEVEL || "info"
 
 const transport = pino.transport({
   targets: [
     {
       level,
-      target: 'pino/file',
+      target: "pino/file",
       options: { destination: `${__dirname}/../../app.log` },
     },
     {
       level,
-      target: 'pino-pretty',
+      target: "pino-pretty",
     },
   ],
-});
+})
 
-export default pino({
-  level,
-  timestamp: pino.stdTimeFunctions.isoTime,
-},
-  transport
-);
+export default pino(
+  {
+    level,
+    timestamp: pino.stdTimeFunctions.isoTime,
+  },
+  transport,
+)
diff --git a/src/lib/models/index.ts b/src/lib/models/index.ts
index dd5144f..145ddce 100644
--- a/src/lib/models/index.ts
+++ b/src/lib/models/index.ts
@@ -1,5 +1,4 @@
-export * from './model';
-export * from "./openai";
+export * from "./model"
+export * from "./openai"
 
-
-export type ModelIds = 'gpt35turbo' | 'gpt4' | 'gpt4turbo';
+export type ModelIds = "gpt35turbo" | "gpt4" | "gpt4turbo"
diff --git a/src/lib/models/model.ts b/src/lib/models/model.ts
index 57dd58d..324e81e 100644
--- a/src/lib/models/model.ts
+++ b/src/lib/models/model.ts
@@ -1,18 +1,17 @@
-import { OpenAIModelParams } from "./openai";
-import { TrialResult } from "../experiments";
+import { OpenAIModelParams } from "./openai"
+import { TrialResult } from "../experiments"
 
 export class Model {
-  modelId: string;
-  makeRequest: (prompt: string, params: ModelParams) => Promise<TrialResult>;
+  modelId: string
+  makeRequest: (prompt: string, params: ModelParams) => Promise<TrialResult>
 
   constructor(
     modelId: string,
-    makeRequest: (prompt: string, params: ModelParams) => Promise<TrialResult>
+    makeRequest: (prompt: string, params: ModelParams) => Promise<TrialResult>,
   ) {
-    this.modelId = modelId;
-    this.makeRequest = makeRequest;
+    this.modelId = modelId
+    this.makeRequest = makeRequest
   }
 }
 
-export type ModelParams = OpenAIModelParams;
-
+export type ModelParams = OpenAIModelParams
diff --git a/src/lib/models/openai.ts b/src/lib/models/openai.ts
index 2d3ffc4..e295fd7 100644
--- a/src/lib/models/openai.ts
+++ b/src/lib/models/openai.ts
@@ -1,56 +1,60 @@
-import OpenAI from "openai";
-import { Model } from "./model";
-import logger from "../logger";
-import 'dotenv/config';
+import OpenAI from "openai"
+import { Model } from "./model"
+import logger from "../logger"
+import "dotenv/config"
 
 const configuration = {
   apiKey: process.env.OPENAI_API_KEY,
-};
-
+}
 
 export interface OpenAIModelParams {
   function: OpenAI.Chat.Completions.ChatCompletionCreateParams.Function
 }
 
 if (!configuration.apiKey) {
-  logger.error("OpenAI API key not configured, please follow instructions in README.md");
+  logger.error(
+    "OpenAI API key not configured, please follow instructions in README.md",
+  )
 } else {
-  logger.info("OpenAI API key loaded from environment variable");
+  logger.info("OpenAI API key loaded from environment variable")
 }
-const openai = new OpenAI(configuration);
-
+const openai = new OpenAI(configuration)
 
 const buildModel = (openai: OpenAI, modelId: string) => {
-  const makeRequest = async function(prompt: string, params: OpenAIModelParams) {
+  const makeRequest = async function (
+    prompt: string,
+    params: OpenAIModelParams,
+  ) {
     const completion = await openai.chat.completions.create({
       model: modelId,
       messages: [
         { role: "system", content: "You are a helpful recipe assistant." },
         {
-          role: 'user',
+          role: "user",
           content: prompt,
-
-        }
+        },
+      ],
+      tools: [
+        {
+          type: "function",
+          // omitting description seems to yield better results
+          function: {
+            name: params.function.name,
+            parameters: params.function.parameters,
+          },
+        },
       ],
-      tools: [{
-        type: 'function',
-        // omitting description seems to yield better results
-        function: {
-          name: params.function.name,
-          parameters: params.function.parameters
-        }
-      }],
       tool_choice: {
-        type: 'function',
-        function: { name: params.function.name }
+        type: "function",
+        function: { name: params.function.name },
       },
-    });
-    return { type: 'openai' as const, data: completion };
-  };
+    })
+    return { type: "openai" as const, data: completion }
+  }
 
-  return new Model(modelId, makeRequest);
+  return new Model(modelId, makeRequest)
 }
 
-export const gpt35turbo = buildModel(openai, "gpt-3.5-turbo-1106");
-export const gpt4 = buildModel(openai, "gpt-4-0613");
-export const gpt4turbo = buildModel(openai, "gpt-4-1106-preview");
+export const gpt35turbo = buildModel(openai, "gpt-3.5-turbo-1106")
+export const gpt4 = buildModel(openai, "gpt-4-0613")
+export const gpt4turbo = buildModel(openai, "gpt-4-1106-preview")
diff --git a/src/lib/types.ts b/src/lib/types.ts
index 098dfd6..a9fcc98 100644
--- a/src/lib/types.ts
+++ b/src/lib/types.ts
@@ -1,94 +1,92 @@
-
 export interface DatasetProfile {
   /**
    * An identifier for the dataset
    */
-  id: string,
+  id: string
 
   /**
    * Metadata for the dataset
    */
-  metadata: Metadata,
+  metadata: Metadata
 
   /**
    * The original instructions given to the annotators
    */
-  originalInstructions?: string,
+  originalInstructions?: string
 
   /**
    * The partitions containing the dataset data
    */
-  partitions: Partition[],
+  partitions: Partition[]
 }
 
 interface Metadata {
   /**
    * The name of the dataset
    */
-  name: string;
+  name: string
 
   /**
    * Web sites containing information about the dataset
    *
    * @items {"type": "string", "format": "uri"}
    */
-  urls: string[],
+  urls: string[]
 
   /**
    * Information about the scientific papers describing the dataset
    */
-  papers: Paper[],
+  papers: Paper[]
 
   /**
    * The date the dataset was published
    *
    * @TJS-pattern ^[0-9]{4}(-[0-9]{2}(-[0-9]{2})?)?$
    */
-  date: string,
+  date: string
 
   /**
    * A description of the dataset
    */
-  description: string,
+  description: string
 
   /**
    * URL(s) to download the dataset files
    *
-   * @items {"type": "string", "format": "uri"} 
+   * @items {"type": "string", "format": "uri"}
    */
-  downloadUrls: string[],
+  downloadUrls: string[]
 
   /**
    * Which type of measures are used to compare the words
    */
-  measureTypes: ('similarity' | 'relatedness')[],
+  measureTypes: ("similarity" | "relatedness")[]
 }
 
-
 export interface Paper {
   /**
    * The title of the paper
    */
-  title: string,
+  title: string
 
   /**
    * The URL where the paper can be found
    *
    * @format uri
    */
-  url?: string,
+  url?: string
 }
 
 interface Partition {
   /**
    * An identifier for the partition
    */
-  id: string,
+  id: string
 
   /**
    * Which type of measure is used to compare the words
    */
-  measureType: 'similarity' | 'relatedness',
+  measureType: "similarity" | "relatedness"
   /**
    * The data for the partition
    */
@@ -99,21 +97,20 @@ type PartitionData = {
   /**
    * The first word in the pair
    */
-  word1: string,
+  word1: string
 
   /**
    * The second word in the pair
    */
-  word2: string,
+  word2: string
 } & (
-    {
+  | {
       /**
        * The averaged numeric value of the semantic measure for the pair
        */
       value: number
-    } |
-    {
-
+    }
+  | {
       /**
        * The individual numeric values of the semantic measure for the pair
        *
@@ -121,4 +118,4 @@ type PartitionData = {
        */
       values: number[]
     }
-  )
+)
diff --git a/src/lib/validation/index.ts b/src/lib/validation/index.ts
index 0901c0e..a0eb737 100644
--- a/src/lib/validation/index.ts
+++ b/src/lib/validation/index.ts
@@ -1,84 +1,90 @@
-import { AggregatedValidationResult } from "../experiments";
+import { AggregatedValidationResult } from "../experiments"
 
-export type ValidationType = 'json-syntax-error' | 'json-schema-error' | 'data-incomplete' | 'data-partially-incorrect' | 'data-incorrect' | 'no-data' | 'data-correct';
+export type ValidationType =
+  | "json-syntax-error"
+  | "json-schema-error"
+  | "data-incomplete"
+  | "data-partially-incorrect"
+  | "data-incorrect"
+  | "no-data"
+  | "data-correct"
 
 export class ValidationResult {
-  type: ValidationType;
-  ok: boolean;
-  data: any;
+  type: ValidationType
+  ok: boolean
+  data: any
 
   constructor(type: ValidationType, ok: boolean, data: any) {
-    this.type = type;
-    this.ok = ok;
-    this.data = data;
+    this.type = type
+    this.ok = ok
+    this.data = data
   }
 }
 
-
 export class JsonSyntaxError extends ValidationResult {
   constructor(data?: any) {
-    super('json-syntax-error', false, data);
+    super("json-syntax-error", false, data)
   }
 }
 
 export class JsonSchemaError extends ValidationResult {
   constructor(data?: any) {
-    super('json-schema-error', false, data);
+    super("json-schema-error", false, data)
   }
 }
 
 export class DataIncomplete extends ValidationResult {
-  percentage: number;
+  percentage: number
 
   constructor(percentage: number, data?: any) {
-    super('data-incomplete', false, data);
-    this.percentage = percentage;
+    super("data-incomplete", false, data)
+    this.percentage = percentage
   }
 }
 
 export class DataPartiallyIncorrect extends ValidationResult {
-  percentage: number;
+  percentage: number
 
   constructor(percentage: number, data?: any) {
-    super('data-partially-incorrect', false, data);
-    this.percentage = percentage;
+    super("data-partially-incorrect", false, data)
+    this.percentage = percentage
   }
 }
 
 export class DataIncorrect extends ValidationResult {
   constructor(data?: any) {
-    super('data-incorrect', false, data);
+    super("data-incorrect", false, data)
   }
 }
 
 export class NoData extends ValidationResult {
   constructor() {
-    super('no-data', false, '');
+    super("no-data", false, "")
   }
 }
 
-
 export class DataCorrect extends ValidationResult {
   constructor(data?: any) {
-    super('data-correct', true, data);
+    super("data-correct", true, data)
   }
 }
 
-
-export async function combineValidations(vs: ValidationResult[]): Promise<AggregatedValidationResult> {
-  let sum = 0;
-  const resultTypes = {} as { [key in ValidationType]: number };
+export async function combineValidations(
+  vs: ValidationResult[],
+): Promise<AggregatedValidationResult> {
+  let sum = 0
+  const resultTypes = {} as { [key in ValidationType]: number }
 
   for (const v of vs) {
-    resultTypes[v.type] = resultTypes[v.type] || 0;
-    resultTypes[v.type]++;
-    if (v.type === 'data-correct') {
-      sum += 1;
+    resultTypes[v.type] = resultTypes[v.type] || 0
+    resultTypes[v.type]++
+    if (v.type === "data-correct") {
+      sum += 1
     }
-    if ('percentage' in v && typeof v.percentage === 'number') {
-      sum += v.percentage;
+    if ("percentage" in v && typeof v.percentage === "number") {
+      sum += v.percentage
     }
   }
 
-  return { avg: sum / vs.length, resultTypes };
+  return { avg: sum / vs.length, resultTypes }
 }
diff --git a/src/scripts/compareMC30.ts b/src/scripts/compareMC30.ts
index 44ead91..92a1f68 100644
--- a/src/scripts/compareMC30.ts
+++ b/src/scripts/compareMC30.ts
@@ -1,19 +1,19 @@
-import { compareMc30 } from "../lib/experiments";
-import { loadDatasetScores } from "../lib/experiments/compare-mc30";
-import logger from "../lib/logger";
+import { compareMc30 } from "../lib/experiments"
+import { loadDatasetScores } from "../lib/experiments/compare-mc30"
+import logger from "../lib/logger"
 
-const trials = process.argv[2] ? parseInt(process.argv[2]) : 1;
+const trials = process.argv[2] ? parseInt(process.argv[2]) : 1
 
 const compareMC30 = async () => {
-  logger.info('Starting')
-  const res = await compareMc30.runTrials(trials);
+  logger.info("Starting")
+  const res = await compareMc30.runTrials(trials)
 
-  const humanScores = await loadDatasetScores();
+  const humanScores = await loadDatasetScores()
 
-  await compareMc30.validate(res, humanScores);
+  await compareMc30.validate(res, humanScores)
 }
 
 compareMC30().then(() => {
-  logger.info('Done');
-  process.exit(0);
-});
+  logger.info("Done")
+  process.exit(0)
+})
diff --git a/src/scripts/dsNameFromDsSample.ts b/src/scripts/dsNameFromDsSample.ts
index eeaa3e2..3d9dd1f 100644
--- a/src/scripts/dsNameFromDsSample.ts
+++ b/src/scripts/dsNameFromDsSample.ts
@@ -1,27 +1,43 @@
-import { DatasetProfile } from "punuy-datasets/src/lib/types";
-import logger from "../lib/logger";
-import { dsNameFromDsSample } from "../lib/experiments";
-import { gpt35turbo, gpt4, gpt4turbo } from "../lib/models";
-import { rg65 } from "punuy-datasets";
+import { DatasetProfile } from "punuy-datasets/src/lib/types"
+import logger from "../lib/logger"
+import { dsNameFromDsSample } from "../lib/experiments"
+import { gpt35turbo, gpt4, gpt4turbo } from "../lib/models"
+import { rg65 } from "punuy-datasets"
 
-const trials = process.argv[2] ? parseInt(process.argv[2]) : 3;
+const trials = process.argv[2] ? parseInt(process.argv[2]) : 3
 
 const nameFromSample = async (ds: DatasetProfile) => {
-  logger.info('Starting')
-  const timestamp = Date.now();
-  const gpt35turbo_res = await dsNameFromDsSample.perform(trials, ds, gpt35turbo, timestamp);
-  const gpt4_res = await dsNameFromDsSample.perform(trials, ds, gpt4, timestamp);
-  const gpt4turbo_res = await dsNameFromDsSample.perform(trials, ds, gpt4turbo, timestamp);
+  logger.info("Starting")
+  const timestamp = Date.now()
+  const gpt35turbo_res = await dsNameFromDsSample.perform(
+    trials,
+    ds,
+    gpt35turbo,
+    timestamp,
+  )
+  const gpt4_res = await dsNameFromDsSample.perform(trials, ds, gpt4, timestamp)
+  const gpt4turbo_res = await dsNameFromDsSample.perform(
+    trials,
+    ds,
+    gpt4turbo,
+    timestamp,
+  )
 
-  logger.info({ ...gpt35turbo_res.combinedResult.resultTypes }, `gpt35turbo_res ${gpt35turbo_res.combinedResult.avg}`);
-  logger.info({ ...gpt4_res.combinedResult.resultTypes }, `gpt4_res ${gpt4_res.combinedResult.avg}`);
-  logger.info({ ...gpt4turbo_res.combinedResult.resultTypes }, `gpt4turbo_res ${gpt4turbo_res.combinedResult.avg}`);
+  logger.info(
+    { ...gpt35turbo_res.combinedResult.resultTypes },
+    `gpt35turbo_res ${gpt35turbo_res.combinedResult.avg}`,
+  )
+  logger.info(
+    { ...gpt4_res.combinedResult.resultTypes },
+    `gpt4_res ${gpt4_res.combinedResult.avg}`,
+  )
+  logger.info(
+    { ...gpt4turbo_res.combinedResult.resultTypes },
+    `gpt4turbo_res ${gpt4turbo_res.combinedResult.avg}`,
+  )
 }
 
 nameFromSample(rg65).then(() => {
-  logger.info('Done');
-  process.exit(0);
-});
-
-
-
+  logger.info("Done")
+  process.exit(0)
+})
diff --git a/src/scripts/dsPaperFromDsName.ts b/src/scripts/dsPaperFromDsName.ts
index b713274..46f2c62 100644
--- a/src/scripts/dsPaperFromDsName.ts
+++ b/src/scripts/dsPaperFromDsName.ts
@@ -1,29 +1,43 @@
-import { DatasetProfile } from "punuy-datasets/src/lib/types";
-import { dsPaperFromDsName } from "../lib/experiments";
-import { gpt35turbo, gpt4, gpt4turbo } from "../lib/models";
-import logger from "../lib/logger";
-import rg65 from "punuy-datasets/rg65";
+import { DatasetProfile } from "punuy-datasets/src/lib/types"
+import { dsPaperFromDsName } from "../lib/experiments"
+import { gpt35turbo, gpt4, gpt4turbo } from "../lib/models"
+import logger from "../lib/logger"
+import rg65 from "punuy-datasets/rg65"
 
-const trials = process.argv[2] ? parseInt(process.argv[2]) : 3;
+const trials = process.argv[2] ? parseInt(process.argv[2]) : 3
 
 const paperFromName = async (ds: DatasetProfile) => {
-
-  logger.info('Starting')
-  const timestamp = Date.now();
-  const gpt35turbo_res = await dsPaperFromDsName.perform(trials, ds, gpt35turbo, timestamp);
-  const gpt4_res = await dsPaperFromDsName.perform(trials, ds, gpt4, timestamp);
-  const gpt4turbo_res = await dsPaperFromDsName.perform(trials, ds, gpt4turbo, timestamp);
-
-  logger.info({ ...gpt35turbo_res.combinedResult.resultTypes }, `gpt35turbo_res ${gpt35turbo_res.combinedResult.avg}`);
-  logger.info({ ...gpt4_res.combinedResult.resultTypes }, `gpt4_res ${gpt4_res.combinedResult.avg}`);
-  logger.info({ ...gpt4turbo_res.combinedResult.resultTypes }, `gpt4turbo_res ${gpt4turbo_res.combinedResult.avg}`);
+  logger.info("Starting")
+  const timestamp = Date.now()
+  const gpt35turbo_res = await dsPaperFromDsName.perform(
+    trials,
+    ds,
+    gpt35turbo,
+    timestamp,
+  )
+  const gpt4_res = await dsPaperFromDsName.perform(trials, ds, gpt4, timestamp)
+  const gpt4turbo_res = await dsPaperFromDsName.perform(
+    trials,
+    ds,
+    gpt4turbo,
+    timestamp,
+  )
+
+  logger.info(
+    { ...gpt35turbo_res.combinedResult.resultTypes },
+    `gpt35turbo_res ${gpt35turbo_res.combinedResult.avg}`,
+  )
+  logger.info(
+    { ...gpt4_res.combinedResult.resultTypes },
+    `gpt4_res ${gpt4_res.combinedResult.avg}`,
+  )
+  logger.info(
+    { ...gpt4turbo_res.combinedResult.resultTypes },
+    `gpt4turbo_res ${gpt4turbo_res.combinedResult.avg}`,
+  )
 }
 
 paperFromName(rg65).then(() => {
-  logger.info('Done');
-  process.exit(0);
-});
-
-
-
-
+  logger.info("Done")
+  process.exit(0)
+})
diff --git a/src/scripts/dsSampleFromDsName.ts b/src/scripts/dsSampleFromDsName.ts
index e4422e4..641dfc0 100644
--- a/src/scripts/dsSampleFromDsName.ts
+++ b/src/scripts/dsSampleFromDsName.ts
@@ -1,26 +1,43 @@
-import { DatasetProfile } from "punuy-datasets/src/lib/types";
-import { dsSampleFromDsName, saveExperimentData } from "../lib/experiments";
-import { gpt35turbo, gpt4, gpt4turbo } from "../lib/models";
-import { rg65 } from "punuy-datasets";
-import logger from "../lib/logger";
+import { DatasetProfile } from "punuy-datasets/src/lib/types"
+import { dsSampleFromDsName, saveExperimentData } from "../lib/experiments"
+import { gpt35turbo, gpt4, gpt4turbo } from "../lib/models"
+import { rg65 } from "punuy-datasets"
+import logger from "../lib/logger"
 
-const trials = process.argv[2] ? parseInt(process.argv[2]) : 3;
+const trials = process.argv[2] ? parseInt(process.argv[2]) : 3
 
 const sampleFromName = async (ds: DatasetProfile) => {
+  logger.info("Starting")
+  const timestamp = Date.now()
+  const gpt35turbo_res = await dsSampleFromDsName.perform(
+    trials,
+    ds,
+    gpt35turbo,
+    timestamp,
+  )
+  const gpt4_res = await dsSampleFromDsName.perform(trials, ds, gpt4, timestamp)
+  const gpt4turbo_res = await dsSampleFromDsName.perform(
+    trials,
+    ds,
+    gpt4turbo,
+    timestamp,
+  )
 
-  logger.info('Starting')
-  const timestamp = Date.now();
-  const gpt35turbo_res = await dsSampleFromDsName.perform(trials, ds, gpt35turbo, timestamp);
-  const gpt4_res = await dsSampleFromDsName.perform(trials, ds, gpt4, timestamp);
-  const gpt4turbo_res = await dsSampleFromDsName.perform(trials, ds, gpt4turbo, timestamp);
-
-  logger.info({ ...gpt35turbo_res.combinedResult.resultTypes }, `gpt35turbo_res ${gpt35turbo_res.combinedResult.avg}`);
-  logger.info({ ...gpt4_res.combinedResult.resultTypes }, `gpt4_res ${gpt4_res.combinedResult.avg}`);
-  logger.info({ ...gpt4turbo_res.combinedResult.resultTypes }, `gpt4turbo_res ${gpt4turbo_res.combinedResult.avg}`);
+  logger.info(
+    { ...gpt35turbo_res.combinedResult.resultTypes },
+    `gpt35turbo_res ${gpt35turbo_res.combinedResult.avg}`,
+  )
+  logger.info(
+    { ...gpt4_res.combinedResult.resultTypes },
+    `gpt4_res ${gpt4_res.combinedResult.avg}`,
+  )
+  logger.info(
+    { ...gpt4turbo_res.combinedResult.resultTypes },
+    `gpt4turbo_res ${gpt4turbo_res.combinedResult.avg}`,
+  )
 }
 
-
 sampleFromName(rg65).then(() => {
-  logger.info('Done');
-  process.exit(0);
-});
+  logger.info("Done")
+  process.exit(0)
+})
diff --git a/src/scripts/dsSampleFromDsSample.ts b/src/scripts/dsSampleFromDsSample.ts
index 9162ef3..1c112e7 100644
--- a/src/scripts/dsSampleFromDsSample.ts
+++ b/src/scripts/dsSampleFromDsSample.ts
@@ -1,26 +1,48 @@
-import { DatasetProfile } from "punuy-datasets/src/lib/types";
-import logger from "../lib/logger";
-import { gpt35turbo, gpt4, gpt4turbo } from "../lib/models";
-import { dsSampleFromDsSample } from "../lib/experiments";
-import { rg65 } from "punuy-datasets";
+import { DatasetProfile } from "punuy-datasets/src/lib/types"
+import logger from "../lib/logger"
+import { gpt35turbo, gpt4, gpt4turbo } from "../lib/models"
+import { dsSampleFromDsSample } from "../lib/experiments"
+import { rg65 } from "punuy-datasets"
 
-
-const trials = process.argv[2] ? parseInt(process.argv[2]) : 3;
+const trials = process.argv[2] ? parseInt(process.argv[2]) : 3
 
 const sampleFromSample = async (ds: DatasetProfile) => {
-  logger.info('Starting')
-  const timestamp = Date.now();
-  const gpt35turbo_res = await dsSampleFromDsSample.perform(trials, ds, gpt35turbo, timestamp);
-  const gpt4_res = await dsSampleFromDsSample.perform(trials, ds, gpt4, timestamp);
-  const gpt4turbo_res = await dsSampleFromDsSample.perform(trials, ds, gpt4turbo, timestamp);
+  logger.info("Starting")
+  const timestamp = Date.now()
+  const gpt35turbo_res = await dsSampleFromDsSample.perform(
+    trials,
+    ds,
+    gpt35turbo,
+    timestamp,
+  )
+  const gpt4_res = await dsSampleFromDsSample.perform(
+    trials,
+    ds,
+    gpt4,
+    timestamp,
+  )
+  const gpt4turbo_res = await dsSampleFromDsSample.perform(
+    trials,
+    ds,
+    gpt4turbo,
+    timestamp,
+  )
 
-  logger.info({ ...gpt35turbo_res.combinedResult.resultTypes }, `gpt35turbo_res ${gpt35turbo_res.combinedResult.avg}`);
-  logger.info({ ...gpt4_res.combinedResult.resultTypes }, `gpt4_res ${gpt4_res.combinedResult.avg}`);
-  logger.info({ ...gpt4turbo_res.combinedResult.resultTypes }, `gpt4turbo_res ${gpt4turbo_res.combinedResult.avg}`);
+  logger.info(
+    { ...gpt35turbo_res.combinedResult.resultTypes },
+    `gpt35turbo_res ${gpt35turbo_res.combinedResult.avg}`,
+  )
+  logger.info(
+    { ...gpt4_res.combinedResult.resultTypes },
+    `gpt4_res ${gpt4_res.combinedResult.avg}`,
+  )
+  logger.info(
+    { ...gpt4turbo_res.combinedResult.resultTypes },
+    `gpt4turbo_res ${gpt4turbo_res.combinedResult.avg}`,
+  )
 }
 
 sampleFromSample(rg65).then(() => {
-  logger.info('Done');
-  process.exit(0);
-});
-
+  logger.info("Done")
+  process.exit(0)
+})
diff --git a/tsconfig.json b/tsconfig.json
index c2f1f2e..72406d0 100644
--- a/tsconfig.json
+++ b/tsconfig.json
@@ -1,10 +1,7 @@
 {
   "compilerOptions": {
     "target": "es2016",
-    "lib": [
-      "ES2017",
-      "DOM"
-    ],
+    "lib": ["ES2017", "DOM"],
     "module": "nodenext",
     "resolveJsonModule": true,
     "esModuleInterop": true,
@@ -13,20 +10,13 @@
     "declaration": true,
     "skipLibCheck": true,
     "paths": {
-      "*": [
-        "src/@types/*"
-      ]
+      "*": ["src/@types/*"]
     },
     "baseUrl": "./",
     "outDir": "dist",
     "sourceMap": true,
-    "noEmitOnError": true,
+    "noEmitOnError": true
   },
-  "include": [
-    "src"
-  ],
-  "exclude": [
-    "node_modules",
-    "dist"
-  ]
+  "include": ["src"],
+  "exclude": ["node_modules", "dist"]
 }