Recognition Textual Entailment on Bahasa Using Biplet Individual Comparison and BiLSTM

I. Made Suwija Putra, Daniel Siahaan*, Ahmad Saikhu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

Recognizing Textual Entailment (RTE) is one of the important tasks in Natural Language Processing (NLP). Various approaches have been taken, starting from a simple statistical framework to the neural network (NN) that is currently the mainstay, including RTE in Bahasa Indonesia. Currently, RTE in Bahasa Indonesia has started using the neural network approach, but the value of the resulting accuracy is still less than 77%. This is because the new NN architecture has just accommodated the lexical elements and not yet the syntactical elements of sentences. Syntactical elements in sentences are important components in obtaining the local information contained therein. In RTE, local information is useful for determining how closely related text fragments are. This study proposes a new approach to NN-based Bahasa Indonesia RTE using the Biplet (head-dependency) individual comparison technique. Biplet is generated from the process of word pair dependency. The concept of word pair dependency is used to improve alignment and inference assessment that is optimized by adjusting the weight of the phrase using an attention mechanism. From experiments conducted using the SNLI dataset that has been translated into Bahasa Indonesia (SNLI Indo), it was obtained that the highest training accuracy value is 83.56% with the validation accuracy value is 64.61% for the number of pairs of sentences of 100k.

Original languageEnglish
Title of host publication8th International Conference on Software Engineering and Computer Systems, ICSECS 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages41-46
Number of pages6
ISBN (Electronic)9798350310931
DOIs
Publication statusPublished - 2023
Event8th IEEE International Conference on Software Engineering and Computer Systems, ICSECS 2023 - Penang, Malaysia
Duration: 25 Aug 202327 Aug 2023

Publication series

Name8th International Conference on Software Engineering and Computer Systems, ICSECS 2023

Conference

Conference8th IEEE International Conference on Software Engineering and Computer Systems, ICSECS 2023
Country/TerritoryMalaysia
CityPenang
Period25/08/2327/08/23

Keywords

  • Biplet individual comparison
  • attention mechanism
  • recognizing textual entailment
  • syntactic relation
  • word pair dependency

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