split do_extarctor_overlap to correctly handle overllappine entities

CHANGELOG.rst

@@ -25,6 +25,7 @@ Removed
 
 Fixed
 -----
+- Overlapping entities cause an exception only if the extractor does not support them.
 
 [0.14.3] - 2019-02-01
 ^^^^^^^^^^^^^^^^^^^^^

rasa_nlu/evaluate.py

@@ -1,13 +1,13 @@
 import itertools
-from collections import defaultdict, namedtuple
-
 import json
-import os
 import logging
-import numpy as np
+import os
 import shutil
+from collections import defaultdict, namedtuple
 from typing import List, Optional, Text
 
+import numpy as np
+
 from rasa_nlu import config, training_data, utils
 from rasa_nlu.config import RasaNLUModelConfig
 from rasa_nlu.extractors.crf_entity_extractor import CRFEntityExtractor
@@ -521,10 +521,25 @@ def determine_token_labels(token, entities, extractors):
     return pick_best_entity_fit(token, candidates)
 
 
+def determine_true_token_labels(token, entities):
+    """Determines the token label given entities that do not overlap.
+    Args:
+        token: a single token
+        entities: entities found by a single extractor
+    Returns:
+        entity type
+    """
+    if len(entities) == 0:
+        return "O"
+
+    candidates = find_intersecting_entites(token, entities)
+    return pick_best_entity_fit(token, candidates)
+
+
 def do_extractors_support_overlap(extractors):
     """Checks if extractors support overlapping entities
     """
-    return extractors is None or CRFEntityExtractor.name not in extractors
+    return CRFEntityExtractor.name not in extractors
 
 
 def align_entity_predictions(targets, predictions, tokens, extractors):
@@ -547,7 +562,7 @@ def align_entity_predictions(targets, predictions, tokens, extractors):
     extractor_labels = {extractor: [] for extractor in extractors}
     for t in tokens:
         true_token_labels.append(
-            determine_token_labels(t, targets, None))
+            determine_true_token_labels(t, targets))
         for extractor, entities in entities_by_extractors.items():
             extracted = determine_token_labels(t, entities, extractor)
             extractor_labels[extractor].append(extracted)

rasa_nlu/server.py

@@ -1,7 +1,8 @@
 import argparse
 import logging
-import simplejson
 from functools import wraps
+
+import simplejson
 from klein import Klein
 from twisted.internet import reactor, threads
 from twisted.internet.defer import inlineCallbacks, returnValue

tests/base/test_evaluation.py

@@ -16,6 +16,7 @@
 from rasa_nlu.evaluate import align_entity_predictions
 from rasa_nlu.evaluate import determine_intersection
 from rasa_nlu.evaluate import determine_token_labels
+from rasa_nlu.evaluate import determine_true_token_labels
 from rasa_nlu.config import RasaNLUModelConfig
 from rasa_nlu.tokenizers import Token
 from rasa_nlu import utils
@@ -170,12 +171,12 @@ def test_determine_token_labels_throws_error():
     with pytest.raises(ValueError):
         determine_token_labels(CH_correct_segmentation,
                                [CH_correct_entity,
-                                CH_wrong_entity], ["ner_crf"])
+                                CH_wrong_entity], ["A", "B", "ner_crf"])
 
 
 def test_determine_token_labels_no_extractors():
-    determine_token_labels(CH_correct_segmentation[0],
-                           [CH_correct_entity, CH_wrong_entity], None)
+    determine_true_token_labels(CH_correct_segmentation[0],
+                                [CH_correct_entity, CH_wrong_entity])
 
 
 def test_determine_token_labels_with_extractors():
@@ -259,7 +260,6 @@ def test_run_cv_evaluation():
 
 
 def test_intent_evaluation_report(tmpdir_factory):
-
     path = tmpdir_factory.mktemp("evaluation").strpath
     report_folder = os.path.join(path, "reports")
     report_filename = os.path.join(report_folder, "intent_report.json")
@@ -297,7 +297,6 @@ def test_intent_evaluation_report(tmpdir_factory):
 
 
 def test_entity_evaluation_report(tmpdir_factory):
-
     path = tmpdir_factory.mktemp("evaluation").strpath
     report_folder = os.path.join(path, "reports")