Stanford CoreNLP wrapper for Apache Spark
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Stanford CoreNLP wrapper for Apache Spark

This package wraps Stanford CoreNLP annotators as Spark DataFrame functions following the simple APIs introduced in Stanford CoreNLP 3.7.0.

This package requires Java 8 and CoreNLP to run. Users must include CoreNLP model jars as dependencies to use language models.

All functions are defined under com.databricks.spark.corenlp.functions.

  • cleanxml: Cleans XML tags in a document and returns the cleaned document.
  • tokenize: Tokenizes a sentence into words.
  • ssplit: Splits a document into sentences.
  • pos: Generates the part of speech tags of the sentence.
  • lemma: Generates the word lemmas of the sentence.
  • ner: Generates the named entity tags of the sentence.
  • depparse: Generates the semantic dependencies of the sentence and returns a flattened list of (source, sourceIndex, relation, target, targetIndex, weight) relation tuples.
  • coref: Generates the coref chains in the document and returns a list of (rep, mentions) chain tuples, where mentions are in the format of (sentNum, startIndex, mention).
  • natlog: Generates the Natural Logic notion of polarity for each token in a sentence, returned as up, down, or flat.
  • openie: Generates a list of Open IE triples as flat (subject, relation, target, confidence) tuples.
  • sentiment: Measures the sentiment of an input sentence on a scale of 0 (strong negative) to 4 (strong positive).

Users can chain the functions to create pipeline, for example:

import org.apache.spark.sql.functions._
import com.databricks.spark.corenlp.functions._

val input = Seq(
  (1, "<xml>Stanford University is located in California. It is a great university.</xml>")
).toDF("id", "text")

val output = input
  .select('sen, tokenize('sen).as('words), ner('sen).as('nerTags), sentiment('sen).as('sentiment)) = false)
|sen                                           |words                                                 |nerTags                                           |sentiment|
|Stanford University is located in California .|[Stanford, University, is, located, in, California, .]|[ORGANIZATION, ORGANIZATION, O, O, O, LOCATION, O]|1        |
|It is a great university .                    |[It, is, a, great, university, .]                     |[O, O, O, O, O, O]                                |4        |


Because CoreNLP depends on protobuf-java 3.x but Spark 2.3 depends on protobuf-java 2.x, we release spark-corenlp as an assembly jar that includes CoreNLP as well as its transitive dependencies, except protobuf-java being shaded. This might cause issues if you have CoreNLP or its dependencies on the classpath.

To use spark-corenlp, you need one of the CoreNLP language models:

# Download one of the language models. 
# Run spark-shell 
spark-shell --packages databricks/spark-corenlp:0.3.1-s_2.11 --jars stanford-corenlp-3.9.1-models.jar


Many thanks to Jason Bolton from the Stanford NLP Group for API discussions.