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org.clojurenlp.core

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Natural language processing in Clojure based on the Stanford-CoreNLP parser.

👋 MAINTAINERS WANTED!

We need help getting this project moving. Please feel free to email to leontalbot@gmail.com to join the org, or drop a line in the chat room.

This is a work in progress, currently in the POC phase.

Usage

Tokenization

(use 'org.clojurenlp.core)
(tokenize "This is a simple sentence.")
;; => '({:token "This", :start-offset 0, :end-offset 4}
        {:token "is", :start-offset 5, :end-offset 7}
        {:token "a", :start-offset 8, :end-offset 9}
        {:token "simple", :start-offset 10, :end-offset 16}
        {:token "sentence", :start-offset 17, :end-offset 25}
        {:token ".", :start-offset 25, :end-offset 26})

Part-of-Speech Tagging

To get a list of TaggedWord objects:

(use 'org.clojurenlp.core)
;;  use any of these:
(-> "Short and sweet." tokenize pos-tag)
(-> "Short and sweet." split-sentences first pos-tag)
(-> ["Short" "and" "sweet" "."] pos-tag)
(-> "Short and sweet." pos-tag)

;; => [#<TaggedWord Short/JJ> #<TaggedWord and/CC> ...]

To return a tag string from TaggedWord object:

(->> "Short and sweet." tokenize pos-tag first .tag)
;; => JJ
(->> "Short and sweet." tokenize pos-tag (map #(.tag %)))
;; => ("JJ" "CC" "JJ" ".")

For more information, see the relevant Javadoc

Named Entity Recognition

To tag named entities utilizing standard Stanford NER model:

(use 'org.clojurenlp.core)
(def pipeline (initialize-pipeline))
(def text "The United States of America will be tagged as a location")
(tag-ner pipeline text)

Training your own model How to Train Your Own Model

To tag named entities utilizing custom trained model:

(use 'org.clojurenlp.core)
(def pipeline (initialize-pipeline "path-to-serialized-model"))
(def text "The United States of America will be tagged as a location")
(tag-ner pipeline text)

Utilizing either NER tagging strategy, a map containing the original text, sentences, tokens, and ner tags will be returned.

Parsing

To parse a sentence:

(use 'org.clojurenlp.core)
(parse (tokenize text))

You will get back a LabeledScoredTreeNode which you can plug in to other Stanford CoreNLP functions or can convert to a standard Treebank string with:

(str (parse (tokenize text)))

Stanford Dependencies

(dependency-graph "I like cheese.")

will parse the sentence and return the dependency graph as a loom graph, which you can then traverse with standard graph algorithms like shortest path, etc. You can also view it:

(def graph (dependency-graph "I like cheese."))
(use 'loom.io)
(view graph)

This requires GraphViz to be installed.

License

© 2018 The ClojureNLP Organization and Contributors

Distributed under the Apache 2.0 License. See LICENSE for details.

The ClojureNLP Organization

  • Leon Talbot @leontalbot
  • Andrew McLoud @andrewmcloud

Contributors

  • Cory Giles
  • Hans Engel
  • Damien Stanton
  • Andrew McLoud
  • Leon Talbot
  • Marek Owsikowski

donation