Evaluating GPT-3.5's Awareness and Summarization Abilities for European Constitutional Texts with Shared Topics
Fuente:
arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866916105726984192 |
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| author | Greco, Candida M. Tagarelli, A. |
| author_facet | Greco, Candida M. Tagarelli, A. |
| contents | Constitutions are foundational legal documents that underpin the governmental and societal structures. As such, they are a reflection of a nation's cultural and social uniqueness, but also contribute to establish topics of universal importance, like citizens' rights and duties (RD). In this work, using the renowned GPT-3.5, we leverage generative large language models to understand constitutional passages that transcend national boundaries. A key contribution of our study is the introduction of a novel application of abstractive summarization on a multi-source collection of constitutional texts, with a focus on European countries' constitution passages related to RD topics. Our results show the meaningfulness of GPT-3.5 to produce informative, coherent and faithful summaries capturing RD topics across European countries. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_14524 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Evaluating GPT-3.5's Awareness and Summarization Abilities for European Constitutional Texts with Shared Topics Greco, Candida M. Tagarelli, A. Computation and Language Artificial Intelligence Computers and Society Digital Libraries Physics and Society Constitutions are foundational legal documents that underpin the governmental and societal structures. As such, they are a reflection of a nation's cultural and social uniqueness, but also contribute to establish topics of universal importance, like citizens' rights and duties (RD). In this work, using the renowned GPT-3.5, we leverage generative large language models to understand constitutional passages that transcend national boundaries. A key contribution of our study is the introduction of a novel application of abstractive summarization on a multi-source collection of constitutional texts, with a focus on European countries' constitution passages related to RD topics. Our results show the meaningfulness of GPT-3.5 to produce informative, coherent and faithful summaries capturing RD topics across European countries. |
| title | Evaluating GPT-3.5's Awareness and Summarization Abilities for European Constitutional Texts with Shared Topics |
| topic | Computation and Language Artificial Intelligence Computers and Society Digital Libraries Physics and Society |
| url | https://arxiv.org/abs/2401.14524 |