Publication Type:

Journal Article

Source:

(2015)

Keywords:

Named Entity Recognition (NER); Natural Language Processing (NLP); Conditional Random Fields (CRF). Entity Extraction from Social Media Text -Indian Languages (ESM-IL);

Abstract:

This proposed method implements the Named Entity Recognition (NER) for four dialects Such as English, Tamil, Malayalam, and Hindi. The results obtained from this work are submitted to a research evaluation workshop Forum for Information Retrieval and Evaluation (FIRE 2015). It is single-layered problem which is divided into multi- layered this step is called pre-processing; it has three levels of named entity tags which are referred as BIO format. This format is trained using Condition Random field(CRF) are used for implementing in NER system , the results obtained are grouped back to single-label or single-tagged referred as Format converting. In FIRE 2015, we developed English, Tamil, Malayalam, and Hindi NER system using CRF. The FIRE estimated the average precision for all the four languages.

Cite this Research Publication

S. P. Sanjay, Dr. M. Anand Kumar, and Soman, K. P., “AMRITA_CEN-NLP@ FIRE 2015: CRF BASED NAMED ENTITY EXTRATION FOR TWITTER MICROPOSTS”, 2015.

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