S. Athira, T. S. Lekshmi, Rajeev R R, E. Sherly, P. C. Reghuraj
{"title":"Pronominal anaphora resolution using salience score for Malayalam","authors":"S. Athira, T. S. Lekshmi, Rajeev R R, E. Sherly, P. C. Reghuraj","doi":"10.1109/COMPSC.2014.7032619","DOIUrl":null,"url":null,"abstract":"Anaphora resolution (AR) is the process of resolving references to an entity in the discourse. The paper presents an algorithm to identify the pronominals and its antecedents in the Malayalam text input. Anaphora resolution is achieved by employing a hybrid of statistical machine learning and rule based approaches. The system is implemented by exploiting the morphological richness of the language and it makes use of parts of speech tagging, subject-object identification and person-number-gender of the NPs. We outline a simple, efficient but a naive algorithm for anaphora resolution, which computes the salience value score for each antecedents. The system performance is evaluated with precision, recall measures which produced promising results. The anaphora resolution system itself can improve the performance of many NLP applications such as text summarisation, text categorisation and term extraction.","PeriodicalId":388270,"journal":{"name":"2014 First International Conference on Computational Systems and Communications (ICCSC)","volume":"89 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 First International Conference on Computational Systems and Communications (ICCSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/COMPSC.2014.7032619","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
Anaphora resolution (AR) is the process of resolving references to an entity in the discourse. The paper presents an algorithm to identify the pronominals and its antecedents in the Malayalam text input. Anaphora resolution is achieved by employing a hybrid of statistical machine learning and rule based approaches. The system is implemented by exploiting the morphological richness of the language and it makes use of parts of speech tagging, subject-object identification and person-number-gender of the NPs. We outline a simple, efficient but a naive algorithm for anaphora resolution, which computes the salience value score for each antecedents. The system performance is evaluated with precision, recall measures which produced promising results. The anaphora resolution system itself can improve the performance of many NLP applications such as text summarisation, text categorisation and term extraction.