Natural Language Processing (NLP) Framework

An Natural Language Processing (NLP) Framework is a data processing framework that can be used to create NLP Systems.

• Context:
  • It can be provided by a Cloud-based NLP Framework to being an On-Premise-based NLP Framework.
  • It can have Pre-Trained Models.
  • It can allow new models training using Training Dataset.
  • It can ... an NLP Platform.
  • It can ... an NLP Library.
  • …
• Example(s):
  • IBM Watson NLP Framework (within IBM Watson System).
  • Amazon NLP Framework [1].
  • GATE NLP Framework.
  • AllenNLP.
  • Gensim.
  • SpaCy.
  • NLTK.
  • OpenNLP.
  • LingPipe.
  • SRILM.
  • MALLET.
  • Stanford Core NLP [2].
  • word2vec.
  • …
• Counter-Example(s):
  • a Machine Learning Toolkit.
  • a Graphing Toolkit.
  • a Visual Processing Platform.
  • …
• See: Semantic Search.
• See: NLP Framework, ML Toolkit.

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References

2016

• (Osborne et al., 2016) ⇒ Francesco Osborne, Helene de Ribaupierre, and Enrico Motta. (2016). “TechMiner: Extracting Technologies from Academic Publications.” In: Proceedings of 20th International Conference on Knowledge Engineering and Knowledge Management (EKAW 2016).
  • QUOTE: ... TM processes the text of the abstracts by means of GATE, a well-known open source NLP platform, and a number of GATE plugins: OWLIM2, a module for importing ontologies, ANNIE, a component that forms a pipeline composed of a tokenizer, a gazetteer, a sentence splitter and a part-of-speech tagger, and JAPE (Java Annotation Patterns Engine), a grammar language for operating over annotations based on regular expressions.

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