Language & NLP
Tag, measure, summarise and classify natural language.
10 live · 0 planned
- Find what a document is about3 CR credits per calloperationalThe phrases that actually characterise a document, ranked, without you reading it first.POST /v1/nlp/keyword-extract
- Work out what language text is in3 CR credits per calloperationalThe language, with a confidence figure, from as little as a sentence.POST /v1/nlp/language-detect
- Reduce words to their base form3 CR credits per calloperational'Running' becomes 'run', so counts group the way a reader would expect.POST /v1/nlp/lemmatize
- Find the names in some text3 CR credits per calloperationalPeople, places and organisations pulled out and labelled.POST /v1/nlp/named-entities
- Label the grammar of a sentence3 CR credits per calloperationalEvery word tagged as a noun, verb, adjective and so on — the first step in most text analysis.POST /v1/nlp/pos-tag
- See how hard text is to read3 CR credits per calloperationalFlesch, Gunning fog and the rest, with the reading age each one implies.POST /v1/nlp/readability-score
- Drop the filler words3 CR credits per calloperationalThe, and, of and their friends removed, leaving the words that carry the meaning.POST /v1/nlp/stopword-strip
- Judge the tone of some text3 CR credits per calloperationalPositive, negative or neutral, overall and sentence by sentence, with a score attached.POST /v1/nlp/sentiment
- Cut text down to its main points3 CR credits per calloperationalThe handful of sentences that carry the document, selected from the original — nothing invented.POST /v1/nlp/summarize-extractive
- Split text into words or sentences3 CR credits per calloperationalSentence and word boundaries done properly, including abbreviations and decimals.POST /v1/nlp/tokenize