Bitext Part-Of-Speech Tagger assigns to each word within a sentence a part of speech such as noun, verb, adverb etc. in more than 20 languages to solve disambiguation and make your work easier.

POS Tagger helps you taking the context of the word into account to provide to the user only the relevant POS for that specific context. Everyone thinks that "spoke" is the past of the verb to speak, however in the sentence: “The front wheel has a broken spoke” we will provide the following analysis.

“In English is not that common but in inflectional languages like Spanish or Russian” is key if you want your machine learning technology to work properly when using text.

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All languages have ambiguous words, which different meanings depending on their position within a sentence, like “can” as verb or “can” as noun, “like” as preposition or “like” as a verb. This might create confusion and noise. POS tagging service provides you the basic information of each word so you speed up your time while dealing with corpuses no matter the final application

POS Tagging Applications

POS tagging is a very popular technique in the NLP community for analyzing text with a finer granularity and accuracy. Bitext POS Tagger can be used for different Machine Learning tasks like:

  • Enriching training text

  • Text clustering or classification

  • Topic modelling

  • Bot training

  • Preprocessor for parser

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