Difference between revisions of "Natural Language Tools & Services"

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(Capability (other))
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** [http://azure.microsoft.com/en-us/services/cognitive-services/ Azure Cognitive Services | Microsoft]
 
** [http://azure.microsoft.com/en-us/services/cognitive-services/ Azure Cognitive Services | Microsoft]
 
** [http://azure.microsoft.com/en-us/services/cognitive-services/speech-services/ Azure Bing Speech API | Microsoft]
 
** [http://azure.microsoft.com/en-us/services/cognitive-services/speech-services/ Azure Bing Speech API | Microsoft]
* [http://stanfordnlp.github.io/CoreNLP/ CoreNLP | Stanford] The Stanford Natural Language Processing Group Toolkit ([[Python]])
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* Standford:
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** [http://stanfordnlp.github.io/CoreNLP/ CoreNLP | Stanford] The Stanford Natural Language Processing Group Toolkit ([[Python]])
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** [http://www.infoq.com/news/2020/03/stanza-nlp-toolkit/ Stanza: A Python NLP Toolkit]. Stanza features both a language-agnostic fully neural pipeline for text analysis (supporting 66 human languages), and a python interface to Stanford's CoreNLP java software
 
* [[Natural Language Toolkit (NLTK)]] ([[Python]]) implements [[Natural Language Processing (NLP)#Text Classification|Text Classification]], [[Natural Language Processing (NLP)#Tokenization / Sentence Splitting|Tokenization / Sentence Splitting]], [[Natural Language Processing (NLP)#Stemming (Morphological Similarity)|Stemming (Morphological Similarity)]], [[Natural Language Processing (NLP)#Part-of-Speech (POS) Tagging|Part-of-Speech (POS) Tagging]], [[Natural Language Processing (NLP)#Syntax (Parsing)|Syntax (Parsing)]], and semantic reasoning
 
* [[Natural Language Toolkit (NLTK)]] ([[Python]]) implements [[Natural Language Processing (NLP)#Text Classification|Text Classification]], [[Natural Language Processing (NLP)#Tokenization / Sentence Splitting|Tokenization / Sentence Splitting]], [[Natural Language Processing (NLP)#Stemming (Morphological Similarity)|Stemming (Morphological Similarity)]], [[Natural Language Processing (NLP)#Part-of-Speech (POS) Tagging|Part-of-Speech (POS) Tagging]], [[Natural Language Processing (NLP)#Syntax (Parsing)|Syntax (Parsing)]], and semantic reasoning
 
** [http://textblob.readthedocs.io/en/dev/ TextBlob]([[Python]]) is kind of an extension of [[Natural Language Toolkit (NLTK)| NLTK]]. You can access many of [[Natural Language Toolkit (NLTK)| NLTK]]'s functions in a simplified manner; includes functionality from the Pattern library
 
** [http://textblob.readthedocs.io/en/dev/ TextBlob]([[Python]]) is kind of an extension of [[Natural Language Toolkit (NLTK)| NLTK]]. You can access many of [[Natural Language Toolkit (NLTK)| NLTK]]'s functions in a simplified manner; includes functionality from the Pattern library

Revision as of 21:38, 29 March 2020

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Text Labeling
  • Bella open tool aimed at simplifying and speeding up text data labeling. Usually, if a dataset was labeled in a CSV file or Google spreadsheets, specialists need to convert it to an appropriate format before model training. Bella’s features and simple interface make it a good substitution to spreadsheets and CSV files. A graphical user interface (GUI) and a database backend for managing labeled data are Bella’s main features.
  • Tagtog choose three approaches: annotate text manually, hire a team that will label data for them, or use machine learning models for automated annotation.
  • Dataturks provides training data preparation tools. Using its products, teams can perform such tasks as parts-of-speech tagging, named-entity recognition tagging, text classification, moderation, and summarization.
  • Brat rapid annotation tool] a web-based tool for text annotation; that is, for adding notes to existing text documents, designed in particular for structured annotation, where the notes are not freeform text but have a fixed form that can be automatically processed and interpreted by a computer.
  • Yedda a lightweight Collaborative Text Span Annotation Tool developed for annotating chunk/entity/event on text (almost all languages including English, Chinese), symbol and even emoji.