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Auteurs principaux: Popov, Dmitrii, Terentev, Egor, Buyanov, Igor
Format: Preprint
Publié: 2024
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Accès en ligne:https://arxiv.org/abs/2410.14074
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author Popov, Dmitrii
Terentev, Egor
Buyanov, Igor
author_facet Popov, Dmitrii
Terentev, Egor
Buyanov, Igor
contents In this work, we investigated how one can use the LLM to transfer the dataset and its annotation from one language to another. This is crucial since sharing the knowledge between different languages could boost certain underresourced directions in the target language, saving lots of efforts in data annotation or quick prototyping. We experiment with English and Russian pairs translating the DEFT corpus. This corpus contains three layers of annotation dedicated to term-definition pair mining, which is a rare annotation type for Russian. We provide a pipeline for the annotation transferring using ChatGPT3.5-turbo and Llama-3.1-8b as core LLMs. In the end, we train the BERT-based models on the translated dataset to establish a baseline.
format Preprint
id arxiv_https___arxiv_org_abs_2410_14074
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Be My Donor. Transfer the NLP Datasets Between the Languages Using LLM
Popov, Dmitrii
Terentev, Egor
Buyanov, Igor
Computation and Language
In this work, we investigated how one can use the LLM to transfer the dataset and its annotation from one language to another. This is crucial since sharing the knowledge between different languages could boost certain underresourced directions in the target language, saving lots of efforts in data annotation or quick prototyping. We experiment with English and Russian pairs translating the DEFT corpus. This corpus contains three layers of annotation dedicated to term-definition pair mining, which is a rare annotation type for Russian. We provide a pipeline for the annotation transferring using ChatGPT3.5-turbo and Llama-3.1-8b as core LLMs. In the end, we train the BERT-based models on the translated dataset to establish a baseline.
title Be My Donor. Transfer the NLP Datasets Between the Languages Using LLM
topic Computation and Language
url https://arxiv.org/abs/2410.14074