SCRQE: Subjective comparative relation quintuple extraction from questions in product domain.
The extraction of subjective comparative relations is essential in the field of question answering systems, playing a crucial role in accurately interpreting and addressing complex questions. To tackle this challenge, we propose the SCQRE model, specifically designed to extract subjective comparativ...
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2025-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0319824 |
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| author | Marzieh Babaali Afsaneh Fatemi Mohammad Ali Nematbakhsh |
| author_facet | Marzieh Babaali Afsaneh Fatemi Mohammad Ali Nematbakhsh |
| author_sort | Marzieh Babaali |
| collection | DOAJ |
| description | The extraction of subjective comparative relations is essential in the field of question answering systems, playing a crucial role in accurately interpreting and addressing complex questions. To tackle this challenge, we propose the SCQRE model, specifically designed to extract subjective comparative relations from questions by focusing on entities, aspects, constraints, and preferences. Our approach leverages multi-task learning, the Natural Language Inference (NLI) paradigm, and a specialized adapter integrated into RoBERTa_base_go_emotions to enhance performance in Element Extraction (EE), Compared Elements Identification (CEI), and Comparative Preference Classification (CPC). Key innovations include handling X- and XOR-type preferences, capturing implicit comparative nuances, and the robust extraction of constraints often neglected in existing models. We also introduce the Smartphone-SCQRE dataset, along with another domain-specific dataset, Brands-CompSent-19-SCQRE, both structured as subjective comparative questions. Experimental results demonstrate that our model outperforms existing approaches across multiple question-level and sentence-level datasets and surpasses recent language models, such as GPT-3.5-turbo-0613, Llama-2-70b-chat, and Qwen-1.5-7B-Chat, showcasing its effectiveness in question-based comparative relation extraction. |
| format | Article |
| id | doaj-art-ee3735fb5ad84be494ec020052f0ec1c |
| institution | OA Journals |
| issn | 1932-6203 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-ee3735fb5ad84be494ec020052f0ec1c2025-08-20T02:23:19ZengPublic Library of Science (PLoS)PLoS ONE1932-62032025-01-01205e031982410.1371/journal.pone.0319824SCRQE: Subjective comparative relation quintuple extraction from questions in product domain.Marzieh BabaaliAfsaneh FatemiMohammad Ali NematbakhshThe extraction of subjective comparative relations is essential in the field of question answering systems, playing a crucial role in accurately interpreting and addressing complex questions. To tackle this challenge, we propose the SCQRE model, specifically designed to extract subjective comparative relations from questions by focusing on entities, aspects, constraints, and preferences. Our approach leverages multi-task learning, the Natural Language Inference (NLI) paradigm, and a specialized adapter integrated into RoBERTa_base_go_emotions to enhance performance in Element Extraction (EE), Compared Elements Identification (CEI), and Comparative Preference Classification (CPC). Key innovations include handling X- and XOR-type preferences, capturing implicit comparative nuances, and the robust extraction of constraints often neglected in existing models. We also introduce the Smartphone-SCQRE dataset, along with another domain-specific dataset, Brands-CompSent-19-SCQRE, both structured as subjective comparative questions. Experimental results demonstrate that our model outperforms existing approaches across multiple question-level and sentence-level datasets and surpasses recent language models, such as GPT-3.5-turbo-0613, Llama-2-70b-chat, and Qwen-1.5-7B-Chat, showcasing its effectiveness in question-based comparative relation extraction.https://doi.org/10.1371/journal.pone.0319824 |
| spellingShingle | Marzieh Babaali Afsaneh Fatemi Mohammad Ali Nematbakhsh SCRQE: Subjective comparative relation quintuple extraction from questions in product domain. PLoS ONE |
| title | SCRQE: Subjective comparative relation quintuple extraction from questions in product domain. |
| title_full | SCRQE: Subjective comparative relation quintuple extraction from questions in product domain. |
| title_fullStr | SCRQE: Subjective comparative relation quintuple extraction from questions in product domain. |
| title_full_unstemmed | SCRQE: Subjective comparative relation quintuple extraction from questions in product domain. |
| title_short | SCRQE: Subjective comparative relation quintuple extraction from questions in product domain. |
| title_sort | scrqe subjective comparative relation quintuple extraction from questions in product domain |
| url | https://doi.org/10.1371/journal.pone.0319824 |
| work_keys_str_mv | AT marziehbabaali scrqesubjectivecomparativerelationquintupleextractionfromquestionsinproductdomain AT afsanehfatemi scrqesubjectivecomparativerelationquintupleextractionfromquestionsinproductdomain AT mohammadalinematbakhsh scrqesubjectivecomparativerelationquintupleextractionfromquestionsinproductdomain |