Text

A large amount of information is available in the form of text. For example, tweets, emails, survey responses, product reviews and so forth contain information that is written in natural language.

The goal of working with text is to convert it into data that can be useful for analysis. Some applications of text analysis include: sentiment analysis, named entity recognition, summarization, and so forth.

The following table lists the plugins currently available for working with text data.

Note

Support level: These plugins are not supported / Tier 2 supported features

Plugin	Description	Language coverage
Text preparation	Detect languages, correct misspellings and clean text data using open source libraries	Language detection: 114 Spell checking: 37 Text cleaning: 59
Text Analysis	Analyze text data with ontology tagging	59 languages
Sentiment analysis	Estimate sentiment polarity (positive/negative) of text data using open source models	English
Text summarization	Automatically summarize text data using open source algorithms to extract sentences	Language-agnostic
Named entity recognition	Extract information on named entities (people, dates, places, etc.) from text data using open source models	7 languages
Speech to Text	Convert speech to text offline using open-source components	English
Amazon Transcribe	Use the Amazon Transcribe API to convert speech to text	40 languages
Sentence embedding	Compute numerical sentence representations for use as feature vectors in a Machine Learning model or for similarity search, using open source models	English
Amazon Comprehend	Use the Amazon Comprehend API for language detection, sentiment analysis, named entity recognition and key phrase extraction	Language detection: 100 Other tasks: 12
Amazon Comprehend Medical	Use the Amazon Comprehend Medical API for Protected Health Information extraction and medical entity recognition	English
Azure Cognitive Services – Text Analytics	Use the Azure Cognitive Services – Text Analytics API for language detection, sentiment analysis, named entity recognition and key phrase extraction	Language detection: 108 Sentiment analysis: 13 Named entity recog.: 23 Key phrase extraction: 16
Crowlingo Multilingual NLP	Use the Crowlingo Multilingual NLP API for language detection, sentiment analysis, summarization and multiple other tasks	102 languages
Google Cloud NLP	Use the Google Cloud NLP API for sentiment analysis, named entity recognition and text classification	Sentiment analysis: 16 Named entity recog.: 11 Text classification: English
Google Cloud Translation	Use the Google Cloud Translation API to translate text	109 languages
Amazon Translation	Use the Amazon Translation API to translate text	71 languages
Azure Translation	Use the Azure Translation API to translate text	90 languages
DeepL Translation	Use the DeepL Translation API to translate text	28 languages
Offline Translation	Translate text offline using open-source components	100 languages
MeaningCloud	Use the MeaningCloud API for language detection, sentiment analysis, topic extraction, summarization and text classification	Language detection: 180 Sentiment analysis: 10 Topic extraction: 13 Summarization: language-agnostic Text classification: 2
NLG Tasks	Use the OpenAI API to perform tasks expressed in natural language, such as Zero-shot Classification or Q&A	English
Tesseract OCR	Perform Optical Character Recognition (OCR) offline using the Tesseract engine	100 languages