@inproceedings{martinez-murillo-etal-2025-gplsicortex,
title = "{GPLSICORTEX} at {S}em{E}val-2025 Task 10: Leveraging Intentions for Generating Narrative Extractions",
author = "Martinez - Murillo, Ivan and
Mir{\'o} Maestre, Mar{\'i}a and
Mart{\'i}nez, Aitana and
Ralund, Snorre and
Lloret, Elena and
Moreda Pozo, Paloma and
Su{\'a}rez Cueto, Armando",
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-1.80/",
pages = "575--583",
ISBN = "979-8-89176-273-2",
abstract = "This paper describes our approach to address the SemEval-2025 Task 10 subtask 3, which is focused on narrative extraction given news articles with a dominant narrative. We design an external knowledge injection approach to fine-tune a Flan-T5 model so the generated narrative explanations are in line with the dominant narrative determined in each text. We also incorporate pragmatic information in the form of communicative intentions, using them as external knowledge to assist the model. This ensures that the generated texts align more closely with the intended explanations and effectively convey the expected meaning. The results show that our approach ranks 3rd in the task leaderboard (0.7428 in Macro-F1) with concise and effective news explanations. The analyses highlight the importance of adding pragmatic information when training systems to generate adequate narrative extractions."
}<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="martinez-murillo-etal-2025-gplsicortex">
<titleInfo>
<title>GPLSICORTEX at SemEval-2025 Task 10: Leveraging Intentions for Generating Narrative Extractions</title>
</titleInfo>
<name type="personal">
<namePart type="given">Ivan</namePart>
<namePart type="family">Martinez - Murillo</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">María</namePart>
<namePart type="family">Miró Maestre</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Aitana</namePart>
<namePart type="family">Martínez</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Snorre</namePart>
<namePart type="family">Ralund</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Elena</namePart>
<namePart type="family">Lloret</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Paloma</namePart>
<namePart type="family">Moreda Pozo</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Armando</namePart>
<namePart type="family">Suárez Cueto</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2025-07</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025)</title>
</titleInfo>
<name type="personal">
<namePart type="given">Sara</namePart>
<namePart type="family">Rosenthal</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Aiala</namePart>
<namePart type="family">Rosá</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Debanjan</namePart>
<namePart type="family">Ghosh</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Marcos</namePart>
<namePart type="family">Zampieri</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>Association for Computational Linguistics</publisher>
<place>
<placeTerm type="text">Vienna, Austria</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
<identifier type="isbn">979-8-89176-273-2</identifier>
</relatedItem>
<abstract>This paper describes our approach to address the SemEval-2025 Task 10 subtask 3, which is focused on narrative extraction given news articles with a dominant narrative. We design an external knowledge injection approach to fine-tune a Flan-T5 model so the generated narrative explanations are in line with the dominant narrative determined in each text. We also incorporate pragmatic information in the form of communicative intentions, using them as external knowledge to assist the model. This ensures that the generated texts align more closely with the intended explanations and effectively convey the expected meaning. The results show that our approach ranks 3rd in the task leaderboard (0.7428 in Macro-F1) with concise and effective news explanations. The analyses highlight the importance of adding pragmatic information when training systems to generate adequate narrative extractions.</abstract>
<identifier type="citekey">martinez-murillo-etal-2025-gplsicortex</identifier>
<location>
<url>https://aclanthology.org/2025.semeval-1.80/</url>
</location>
<part>
<date>2025-07</date>
<extent unit="page">
<start>575</start>
<end>583</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T GPLSICORTEX at SemEval-2025 Task 10: Leveraging Intentions for Generating Narrative Extractions
%A Martinez - Murillo, Ivan
%A Miró Maestre, María
%A Martínez, Aitana
%A Ralund, Snorre
%A Lloret, Elena
%A Moreda Pozo, Paloma
%A Suárez Cueto, Armando
%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 martinez-murillo-etal-2025-gplsicortex
%X This paper describes our approach to address the SemEval-2025 Task 10 subtask 3, which is focused on narrative extraction given news articles with a dominant narrative. We design an external knowledge injection approach to fine-tune a Flan-T5 model so the generated narrative explanations are in line with the dominant narrative determined in each text. We also incorporate pragmatic information in the form of communicative intentions, using them as external knowledge to assist the model. This ensures that the generated texts align more closely with the intended explanations and effectively convey the expected meaning. The results show that our approach ranks 3rd in the task leaderboard (0.7428 in Macro-F1) with concise and effective news explanations. The analyses highlight the importance of adding pragmatic information when training systems to generate adequate narrative extractions.
%U https://aclanthology.org/2025.semeval-1.80/
%P 575-583
Markdown (Informal)
[GPLSICORTEX at SemEval-2025 Task 10: Leveraging Intentions for Generating Narrative Extractions](https://aclanthology.org/2025.semeval-1.80/) (Martinez - Murillo et al., SemEval 2025)
ACL