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Part of Speech (POS) Tagging is the first step in the development of any NLP Application. It is a task which assigns POS labels to words supplied in the text. This is the reason why researchers consider this as a sequence labeling task where words are considered as sequences which needs to be labeled. Each word’s tag is identified within a context using the previous word/tag combination. POS tagging is used in various applications like parsing where word and their tags are transformed into chunks which can be combined to generate the complete parse of a text. Taggers are used in Machine Translation (MT) while developing a transfer based MT Engine. Here, we require the text in the source language to be POS tagged and then parsed which can then be transferred to the target side using transfer grammar. Taggers can also be used in Name Entity Recognition (NER) where a word tagged as a noun (either proper or common noun) is further classified as a name of a person, organization, location, time, date etc.

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POS-Tagger-for-Hindi-Language

Part of Speech (POS) Tagging is the first step in the development of any NLP Application. It is a task which assigns POS labels to words supplied in the text. This is the reason why researchers consider this as a sequence labeling task where words are considered as sequences which needs to be labeled. Each word’s tag is identified within a context using the previous word/tag combination. POS tagging is used in various applications like parsing where word and their tags are transformed into chunks which can be combined to generate the complete parse of a text. Taggers are used in Machine Translation (MT) while developing a transfer based MT Engine. Here, we require the text in the source language to be POS tagged and then parsed which can then be transferred to the target side using transfer grammar. Taggers can also be used in Name Entity Recognition (NER) where a word tagged as a noun (either proper or common noun) is further classified as a name of a person, organization, location, time, date etc.

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