Module: TexterraNLP

Includes:
TexterraNLPSpecs
Included in:
TexterraAPI
Defined in:
lib/ispras-api/texterra/nlp.rb

Constant Summary

Constants included from TexterraNLPSpecs

TexterraNLPSpecs::NLP_SPECS

Instance Method Summary collapse

Instance Method Details

#disambiguation_annotate(text) ⇒ Hash

Detects the most appropriate meanings (concepts) for terms occurred in a given text

Parameters:

  • text (String) —

    Text to process

Returns:

  • (Hash) —

    Texterra document



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# File 'lib/ispras-api/texterra/nlp.rb', line 73

def disambiguation_annotate(text)
  preset_nlp(:disambiguation, text)
end

#domain_detection_annotate(text) ⇒ Hash

Detects the most appropriate domain for the given text. Currently only 2 specific domains are supported: ‘movie’ and ‘politics’ If no domain from this list has been detected, the text is assumed to be no domain, or general domain

Parameters:

  • text (String) —

    Text to process

Returns:

  • (Hash) —

    Texterra document



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# File 'lib/ispras-api/texterra/nlp.rb', line 92

def domain_detection_annotate(text)
  preset_nlp(:domainDetection, text)
end

#domain_polarity_detection_annotate(text, domain = '') ⇒ Hash

Detects whether the given text has positive, negative, or no sentiment, with respect to domain. If domain isn’t provided, Domain detection is applied, this way method tries to achieve best results. If no domain is detected general domain algorithm is applied

Parameters:

  • text (String) —

    Text to process

  • domain (String) (defaults to: '') —

    Domain for polarity detection

Returns:

  • (Hash) —

    Texterra document



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# File 'lib/ispras-api/texterra/nlp.rb', line 119

def domain_polarity_detection_annotate(text, domain = '')
  specs = NLP_SPECS[:domainPolarityDetection]
  domain = "(#{domain})" unless domain.empty?
  result = POST(specs[:path] % domain, specs[:params], {text: text}, :json)
  result[:annotations].each do |key, value|
    value.map! { |an| assign_text(an, text) }
  end
  result
end

#key_concepts_annotate(text) ⇒ Hash

Key concepts are the concepts providing short (conceptual) and informative text description. This service extracts a set of key concepts for a given text

Parameters:

  • text (String) —

    Text to process

Returns:

  • (Hash) —

    Texterra document



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# File 'lib/ispras-api/texterra/nlp.rb', line 82

def key_concepts_annotate(text)
  preset_nlp(:keyConcepts, text)
end

#language_detection_annotate(text) ⇒ Hash

Detects language of given text

Parameters:

  • text (String) —

    Text to process

Returns:

  • (Hash) —

    Texterra document



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# File 'lib/ispras-api/texterra/nlp.rb', line 9

def language_detection_annotate(text)
  preset_nlp(:languageDetection, text)
end

#lemmatization_annotate(text) ⇒ Hash

Detects lemma of each word of a given text

Parameters:

  • text (String) —

    Text to process

Returns:

  • (Hash) —

    Texterra document



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# File 'lib/ispras-api/texterra/nlp.rb', line 33

def lemmatization_annotate(text)
  preset_nlp(:lemmatization, text)
end

#named_entities_annotate(text) ⇒ Hash

Finds all named entities occurences in a given text

Parameters:

  • text (String) —

    Text to process

Returns:

  • (Hash) —

    Texterra document



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# File 'lib/ispras-api/texterra/nlp.rb', line 57

def named_entities_annotate(text)
  preset_nlp(:namedEntities, text)
end

#polarity_detection_annotate(text) ⇒ Hash

Detects whether the given text has positive, negative or no sentiment

Parameters:

  • text (String) —

    Text to process

Returns:

  • (Hash) —

    Texterra document



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# File 'lib/ispras-api/texterra/nlp.rb', line 108

def polarity_detection_annotate(text)
  preset_nlp(:polarityDetection, text)
end

#pos_tagging_annotate(text) ⇒ Hash

Detects part of speech tag for each word of a given text

Parameters:

  • text (String) —

    Text to process

Returns:

  • (Hash) —

    Texterra document



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# File 'lib/ispras-api/texterra/nlp.rb', line 41

def pos_tagging_annotate(text)
  preset_nlp(:posTagging, text)
end

#sentence_detection_annotate(text) ⇒ Hash

Detects boundaries of sentences in a given text

Parameters:

  • text (String) —

    Text to process

Returns:

  • (Hash) —

    Texterra document



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# File 'lib/ispras-api/texterra/nlp.rb', line 17

def sentence_detection_annotate(text)
  preset_nlp(:sentenceDetection, text)
end

#spelling_correction_annotate(text) ⇒ Hash

Tries to correct disprints and other spelling errors in a given text

Parameters:

  • text (String) —

    Text to process

Returns:

  • (Hash) —

    Texterra document



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# File 'lib/ispras-api/texterra/nlp.rb', line 49

def spelling_correction_annotate(text)
  preset_nlp(:spellingCorrection, text)
end

#subjectivity_detection_annotate(text) ⇒ Hash

Detects whether the given text is subjective or not

Parameters:

  • text (String) —

    Text to process

Returns:

  • (Hash) —

    Texterra document



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# File 'lib/ispras-api/texterra/nlp.rb', line 100

def subjectivity_detection_annotate(text)
  preset_nlp(:subjectivityDetection, text)
end

#syntax_detection(text) ⇒ Hash

Detects Syntax relations in text. Only works for russian texts

Parameters:

  • text (String) —

    Text to process

Returns:

  • (Hash) —

    Texterra document



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# File 'lib/ispras-api/texterra/nlp.rb', line 142

def syntax_detection(text)
  result = preset_nlp(:syntaxDetection, text)
  result[:annotations][:'syntax-relation'].each do |an|
    an[:value][:parent] = assign_text(an[:value][:parent], text) if an[:value] && an[:value][:parent]
  end
  result
end

#term_detection_annotate(text) ⇒ Hash

Extracts not overlapping terms within a given text; term is a textual representation for some concept of the real world

Parameters:

  • text (String) —

    Text to process

Returns:

  • (Hash) —

    Texterra document



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# File 'lib/ispras-api/texterra/nlp.rb', line 65

def term_detection_annotate(text)
  preset_nlp(:termDetection, text)
end

#tokenization_annotate(text) ⇒ Hash

Detects all tokens (minimal significant text parts) in a given text

Parameters:

  • text (String) —

    Text to process

Returns:

  • (Hash) —

    Texterra document



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# File 'lib/ispras-api/texterra/nlp.rb', line 25

def tokenization_annotate(text)
  preset_nlp(:tokenization, text)
end

#tweet_normalization(text) ⇒ Hash

Detects Twitter-specific entities: Hashtags, User names, Emoticons, URLs. And also: Stop-words, Misspellings, Spelling suggestions, Spelling corrections

Parameters:

  • text (String) —

    Text to process

Returns:

  • (Hash) —

    Texterra document



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# File 'lib/ispras-api/texterra/nlp.rb', line 134

def tweet_normalization(text)
  preset_nlp(:tweetNormalization, text)
end