{"title":"Bengali noun phrase chunking based on conditional random fields","authors":"K. Sarkar, V. Gayen","doi":"10.1109/ICBIM.2014.6970957","DOIUrl":null,"url":null,"abstract":"Noun phrase (NP) chunking deals with extracting the noun phrases from a sentence. While NP chunking is much simpler than parsing, it is still a challenging task to build an accurate and efficient NP chunker. Noun phrase chunking is an important and useful task in many natural language processing applications. It is studied well for English, however not much work has been done for Bengali. This paper presents a Bengali noun phrase chunking approach based on conditional random fields (CRFs) models. Our developed NP chunker has been tested on the ICON 2013 dataset and achieves an impressive F-score of 95.92.","PeriodicalId":6549,"journal":{"name":"2014 2nd International Conference on Business and Information Management (ICBIM)","volume":"24 1","pages":"148-153"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 2nd International Conference on Business and Information Management (ICBIM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICBIM.2014.6970957","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
Noun phrase (NP) chunking deals with extracting the noun phrases from a sentence. While NP chunking is much simpler than parsing, it is still a challenging task to build an accurate and efficient NP chunker. Noun phrase chunking is an important and useful task in many natural language processing applications. It is studied well for English, however not much work has been done for Bengali. This paper presents a Bengali noun phrase chunking approach based on conditional random fields (CRFs) models. Our developed NP chunker has been tested on the ICON 2013 dataset and achieves an impressive F-score of 95.92.
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