https://github.com/dcavar/nltk-json-nlp

NLTK wrapper to JSON-NLP.
https://github.com/dcavar/nltk-json-nlp

json natural-language-processing nltk

Last synced: about 1 year ago
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NLTK wrapper to JSON-NLP.

• Host: GitHub
• URL: https://github.com/dcavar/nltk-json-nlp
• Owner: dcavar
• License: apache-2.0
• Created: 2019-03-26T21:37:44.000Z (over 7 years ago)
• Default Branch: master
• Last Pushed: 2019-05-25T17:42:00.000Z (about 7 years ago)
• Last Synced: 2025-04-09T17:16:10.660Z (about 1 year ago)
• Topics: json, natural-language-processing, nltk
• Language: Python
• Homepage: https://nlp-lab.org/nltkjsonnlp/
• Size: 45.9 KB
• Stars: 5
• Watchers: 4
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# NLTK-JSON-NLP

(C) 2019 by [Damir Cavar], [Oren Baldinger], Maanvitha Gongalla, Anurag Kumar, Murali Kammili, Boli Fang

Brought to you by the [NLP-Lab.org]!

## Introduction

[NLTK] wrapper to [JSON-NLP]. [NLTK] has a wide variety of capabilities, but for our purposes

we are limiting it to [WordNet], [VerbNet], and [FrameNet]. Other packages such as [spaCy] and 

[Flair] are more accurately able to annotate things like part of speech tags and dependency 

parses. See below for instruction on how to unify outputs from multiple packages.

## Microservice

The [JSON-NLP] repository provides a Microservice class, with a pre-built implementation of [Flask]. To run it, execute:

    

    python nltkjsonnlp/server.py

 

Since `server.py` extends the [Flask] app, a WSGI file would contain:

    from nltkjsonnlp.server import app as application

    

## Pipeline

[JSON-NLP] provides a simple `Pipeline` interface that we implement as `NltkPipeline`:

    

    pipeline = nltkjsonnlp.NltkPipeline()

    print(pipeline.process(text='I am a sentence.'))

            

## Unification

To make the best use of this pipeline, it is best to unify it with a more accurate and complete

pipeline such as [spaCy-NLP-Json]:

    class UnifiedPipeline(pyjsonnlp.pipeline.Pipeline):

        def __init__(self):

            super(UnifiedPipeline, self).__init__()

            self.spacy = spacynlpjson.SpacyPipeline()

            self.nltk = nltkjsonnlp.NltkPipeline()

    

        def process(self, text='', coreferences=True, constituents=False, dependencies=True, expressions=True,

                    **kwargs) -> OrderedDict:

            # start with a spacy parse

            spacy_json = self.spacy.process(text, spacy_model='en_core_web_md', constituents=False,

                                            coreferences=coreferences, dependencies=dependencies, expressions=False)

            # the get an nltk parse

            nltk_json = self.nltk.process(text)

            

            # unify the parses

            return pyjsonnlp.unification.unifier.add_annotation_to_a_from_b(a=spacy_json, 

                                                                            b=nltk_json, annotation='tokens')

[Damir Cavar]: http://damir.cavar.me/ "Damir Cavar"

[Oren Baldinger]: https://oren.baldinger.me/ "Oren Baldinger"

[NLP-Lab.org]: http://nlp-lab.org/ "NLP-Lab.org"

[JSON-NLP]: https://github.com/dcavar/JSON-NLP "JSON-NLP"

[Flair]: https://github.com/zalandoresearch/flair "Flair"

[spaCy]: https://spacy.io/ "spaCy"

[NLTK]: http://nltk.org/ "Natural Language Processing Toolkit"

[Polyglot]: https://github.com/aboSamoor/polyglot "Polyglot" 

[Xrenner]: https://github.com/amir-zeldes/xrenner "Xrenner"

[CONLL-U]: https://universaldependencies.org/format.html "CONLL-U"

[spaCy-NLP-Json]: https://github.com/dcavar/spaCy-JSON-NLP "spaCy-JSON-NLP"

[WordNet]: https://wordnet.princeton.edu/ "Wordnet"

[FrameNet]: https://framenet.icsi.berkeley.edu/fndrupal/ "FrameNet"

[VerbNet]: https://verbs.colorado.edu/~mpalmer/projects/verbnet.html "VerbNet"