@inproceedings{sheeja-s-lalitha-devi-2022-automatic,
title = "Automatic Identification of Explicit Connectives in {M}alayalam",
author = "Sheeja S, Kumari and
Lalitha Devi, Sobha",
editor = "Jha, Girish Nath and
L., Sobha and
Bali, Kalika and
Ojha, Atul Kr.",
booktitle = "Proceedings of the WILDRE-6 Workshop within the 13th Language Resources and Evaluation Conference",
month = jun,
year = "2022",
address = "Marseille, France",
publisher = "European Language Resources Association",
url = "https://aclanthology.org/2022.wildre-1.13/",
pages = "74--79",
abstract = "This work presents an automatic identification of explicit connectives and its arguments using supervised method, Conditional Random Fields (CRFs). In this work, we focus on the identification of connectives and their arguments in the corpus. We consider explicit connectives and its arguments for the present study. The corpus we have considered has 4,000 sentences from Malayalam documents and manually annotated the corpus for POS, chunk, clause, discourse connectives and its arguments. The corpus thus annotated is used for building the base engine. The percentage of the performance of the system is evaluated based on the precision, recall and F-score and obtained encouraging results. We have analysed the errors generated by the system and used the features obtained from the anlaysis to improve the performance of the system"
}
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<abstract>This work presents an automatic identification of explicit connectives and its arguments using supervised method, Conditional Random Fields (CRFs). In this work, we focus on the identification of connectives and their arguments in the corpus. We consider explicit connectives and its arguments for the present study. The corpus we have considered has 4,000 sentences from Malayalam documents and manually annotated the corpus for POS, chunk, clause, discourse connectives and its arguments. The corpus thus annotated is used for building the base engine. The percentage of the performance of the system is evaluated based on the precision, recall and F-score and obtained encouraging results. We have analysed the errors generated by the system and used the features obtained from the anlaysis to improve the performance of the system</abstract>
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%0 Conference Proceedings
%T Automatic Identification of Explicit Connectives in Malayalam
%A Sheeja S, Kumari
%A Lalitha Devi, Sobha
%Y Jha, Girish Nath
%Y L., Sobha
%Y Bali, Kalika
%Y Ojha, Atul Kr.
%S Proceedings of the WILDRE-6 Workshop within the 13th Language Resources and Evaluation Conference
%D 2022
%8 June
%I European Language Resources Association
%C Marseille, France
%F sheeja-s-lalitha-devi-2022-automatic
%X This work presents an automatic identification of explicit connectives and its arguments using supervised method, Conditional Random Fields (CRFs). In this work, we focus on the identification of connectives and their arguments in the corpus. We consider explicit connectives and its arguments for the present study. The corpus we have considered has 4,000 sentences from Malayalam documents and manually annotated the corpus for POS, chunk, clause, discourse connectives and its arguments. The corpus thus annotated is used for building the base engine. The percentage of the performance of the system is evaluated based on the precision, recall and F-score and obtained encouraging results. We have analysed the errors generated by the system and used the features obtained from the anlaysis to improve the performance of the system
%U https://aclanthology.org/2022.wildre-1.13/
%P 74-79
Markdown (Informal)
[Automatic Identification of Explicit Connectives in Malayalam](https://aclanthology.org/2022.wildre-1.13/) (Sheeja S & Lalitha Devi, WILDRE 2022)
ACL