Entity extraction == Named Entity Recognition == This API annotates text and returns identified entities, such as people, locations, dates, products, etc The text also gets classified into predefined or custom categories, such as politics, entertainment->music, technology etc. We are using a huge database of entities (addresses, celebrities, etc) and combining it with pattern recognition approaches. Please contact us if you need custom entities or topics.
This service provides detailed linguistic information for a given text in English, Spanish, French, Italian, Portuguese and Catalan. There are three operating modes that cover different aspects of the morphosyntactic and semantic analysis: Lemmatization, which provides the lemmas of the different words in a text; PoS tagging: which provides not only the grammatical category of a word, including semantic information about that word; Syntactic analysis: that provides a thorough syntactic analysis, giving a complete syntactic tree where the leaves represent the most basic elements and their morphological and semantic analyses.
TextAnalysis API provides customized Text Analysis,Text Mining and Text Processing Services like Text Summarization, Language Detection, Text Classification, Sentiment Analysis, Word Tokenize, Part-of-Speech(POS) Tagging, Named Entity Recognition(NER), Stemmer, Lemmatizer, Chunker, Parser, Key Phrase Extraction(Noun Phrase Extraction), Sentence Segmentation(Sentence Boundary Detection), Grammar Checker and other Text Analysis Tasks. It stands on the giant shoulders of NLP Tools, such as NLTK, TextBlob, Pattern, MBSP and etc. You can test the services on our demo website TextAnalysisOnline and use the TextAnalysis API on Mashape. If you have any questions or want any customized text analysis services, you can contact us by email: [email protected]
Topics Extraction tags locations, people, companies, dates and many other elements appearing in a text written in Spanish, English, French, Italian, Portuguese or Catalan. This detection process is carried out by combining a number of complex natural language processing techniques that allow to obtain morphological, syntactic and semantic analyses of a text and use them to identify different types of significant elements.