Recognition Textual Entailment on Bahasa Using Biplet Individual Comparison and BiLSTM

Suwija Putra, I Made; Siahaan, Daniel; Saikhu, Ahmad

doi:10.1109/icsecs58457.2023.10256326

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2024

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Cited by 2 publications

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“…The SNLI Indo dataset has been utilized in prior research to develop state-of-the-art Indonesian language RTE models [6 , 7] . In this research, experiments were conducted using neural network approaches, specifically two types of Recurrent Neural Networks (RNN), namely Long Short-Term Memory (LSTM) and Bidirectional (BiLSTM) networks [23] .…”

Section: Experimental Design Materials and Methodsmentioning

confidence: 99%

See 1 more Smart Citation

SNLI Indo: A recognizing textual entailment dataset in Indonesian derived from the Stanford Natural Language Inference dataset

Putra,

Siahaan,

Saikhu

2024

Data in Brief

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Section: Experimental Design Materials and Methodsmentioning

confidence: 99%

“…The SNLI Indo dataset consists of 549,365 sentence pairs for training, 9,840 sentence pairs for model validation, and 9,822 sentence pairs for testing. SNLI Indo has been used in previous researches [6 , 7] .…”

Section: Value Of the Datamentioning

confidence: 99%