@inproceedings{nishi-takagi-2025-wc,
title = "{WC} Team at {S}em{E}val-2025 Task 6: {P}romise{E}val: Multinational, Multilingual, Multi-Industry Promise Verification leveraging monolingual and multilingual {BERT} models",
author = "Nishi, Takumi and
Takagi, Nicole Miu",
editor = "Rosenthal, Sara and
Ros{\'a}, Aiala and
Ghosh, Debanjan and
Zampieri, Marcos",
booktitle = "Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025)",
month = jul,
year = "2025",
address = "Vienna, Austria",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.semeval-1.219/",
pages = "1670--1676",
ISBN = "979-8-89176-273-2",
abstract = "This paper presents our system developed for SemEval-2025 Task 6: PromiseEval: Multinational, Multilingual, Multi-Industry Promise Verification. The task aims at identifying ``promises'' made and ``evidence'' provided in company ESG statements for various languages. Our team participated in Subtasks 1 and 2 for the languages English, French, and Japanese. In this work, we propose using BERT and finetuning it to better address the task. We achieve competitive results, especially for English and Japanese."
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%0 Conference Proceedings
%T WC Team at SemEval-2025 Task 6: PromiseEval: Multinational, Multilingual, Multi-Industry Promise Verification leveraging monolingual and multilingual BERT models
%A Nishi, Takumi
%A Takagi, Nicole Miu
%Y Rosenthal, Sara
%Y Rosá, Aiala
%Y Ghosh, Debanjan
%Y Zampieri, Marcos
%S Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025)
%D 2025
%8 July
%I Association for Computational Linguistics
%C Vienna, Austria
%@ 979-8-89176-273-2
%F nishi-takagi-2025-wc
%X This paper presents our system developed for SemEval-2025 Task 6: PromiseEval: Multinational, Multilingual, Multi-Industry Promise Verification. The task aims at identifying “promises” made and “evidence” provided in company ESG statements for various languages. Our team participated in Subtasks 1 and 2 for the languages English, French, and Japanese. In this work, we propose using BERT and finetuning it to better address the task. We achieve competitive results, especially for English and Japanese.
%U https://aclanthology.org/2025.semeval-1.219/
%P 1670-1676
Markdown (Informal)
[WC Team at SemEval-2025 Task 6: PromiseEval: Multinational, Multilingual, Multi-Industry Promise Verification leveraging monolingual and multilingual BERT models](https://aclanthology.org/2025.semeval-1.219/) (Nishi & Takagi, SemEval 2025)
ACL