Arabic Temporal Common Sense Understanding
Natural language understanding (NLU) includes temporal text understanding, which can be complex and encompasses temporal common sense understanding. There are many challenges in comprehending common sense within a text. Currently, there is a limited number of datasets containing temporal common sens...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-12-01
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| Series: | Computation |
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| Online Access: | https://www.mdpi.com/2079-3197/13/1/5 |
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| author | Reem Alqifari Hend Al-Khalifa Simon O’Keefe |
| author_facet | Reem Alqifari Hend Al-Khalifa Simon O’Keefe |
| author_sort | Reem Alqifari |
| collection | DOAJ |
| description | Natural language understanding (NLU) includes temporal text understanding, which can be complex and encompasses temporal common sense understanding. There are many challenges in comprehending common sense within a text. Currently, there is a limited number of datasets containing temporal common sense in English and there is an absence of such datasets specifically for the Arabic language. In this study, an Arabic dataset was constructed based on an available English dataset. This dataset is considered a valuable resource for the Arabic community. Consequently, different multilingual pre-trained language models (PLMs) were applied to both the English and new Arabic datasets. Based on this, the effectiveness of these models in Arabic and English is compared and discussed. After analyzing the errors, a new categorization of errors was proposed. Finally, the ability of the PLMs to understand the input text and predict temporal features was evaluated. Through this detailed categorization of errors and classification of temporal elements, this study establishes a comprehensive framework aimed at clarifying the specific challenges encountered by PLMs in temporal common sense understanding (TCU). This methodology underscores the urgent need for further research on PLMs’ capabilities for TCU tasks. |
| format | Article |
| id | doaj-art-ca6224e4b6fe44bc839f30af67b78162 |
| institution | Kabale University |
| issn | 2079-3197 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Computation |
| spelling | doaj-art-ca6224e4b6fe44bc839f30af67b781622025-01-24T13:27:46ZengMDPI AGComputation2079-31972024-12-01131510.3390/computation13010005Arabic Temporal Common Sense UnderstandingReem Alqifari0Hend Al-Khalifa1Simon O’Keefe2College of Computer and Information Sciences, King Saud University, Riyadh 11421, Saudi ArabiaCollege of Computer and Information Sciences, King Saud University, Riyadh 11421, Saudi ArabiaDepartment of Computer Science, University of York, York YO10 5GH, UKNatural language understanding (NLU) includes temporal text understanding, which can be complex and encompasses temporal common sense understanding. There are many challenges in comprehending common sense within a text. Currently, there is a limited number of datasets containing temporal common sense in English and there is an absence of such datasets specifically for the Arabic language. In this study, an Arabic dataset was constructed based on an available English dataset. This dataset is considered a valuable resource for the Arabic community. Consequently, different multilingual pre-trained language models (PLMs) were applied to both the English and new Arabic datasets. Based on this, the effectiveness of these models in Arabic and English is compared and discussed. After analyzing the errors, a new categorization of errors was proposed. Finally, the ability of the PLMs to understand the input text and predict temporal features was evaluated. Through this detailed categorization of errors and classification of temporal elements, this study establishes a comprehensive framework aimed at clarifying the specific challenges encountered by PLMs in temporal common sense understanding (TCU). This methodology underscores the urgent need for further research on PLMs’ capabilities for TCU tasks.https://www.mdpi.com/2079-3197/13/1/5common sensetemporal understandingArabic temporal understandingnatural language understandingreading comprehensiontransformers |
| spellingShingle | Reem Alqifari Hend Al-Khalifa Simon O’Keefe Arabic Temporal Common Sense Understanding Computation common sense temporal understanding Arabic temporal understanding natural language understanding reading comprehension transformers |
| title | Arabic Temporal Common Sense Understanding |
| title_full | Arabic Temporal Common Sense Understanding |
| title_fullStr | Arabic Temporal Common Sense Understanding |
| title_full_unstemmed | Arabic Temporal Common Sense Understanding |
| title_short | Arabic Temporal Common Sense Understanding |
| title_sort | arabic temporal common sense understanding |
| topic | common sense temporal understanding Arabic temporal understanding natural language understanding reading comprehension transformers |
| url | https://www.mdpi.com/2079-3197/13/1/5 |
| work_keys_str_mv | AT reemalqifari arabictemporalcommonsenseunderstanding AT hendalkhalifa arabictemporalcommonsenseunderstanding AT simonokeefe arabictemporalcommonsenseunderstanding |