HMM Based Chunker for Hindi

Abstract

This paper presents an HMM-based chunk tagger for Hindi. Various tagging schemes for marking chunk boundaries are discussed along with their results. Contextual information is incorporated into the chunk tags in the form of partof- speech (POS) information. This information is also added to the tokens themselves to achieve better precision. Error analysis is carried out to reduce the number of common errors. It is found that for certain classes of words, using the POS information is more effective than using a combination of word and POS tag as the token. Finally, chunk labels are also marked on the chunks.