Abstract
One common mistake made by non-native speakers of English is to drop the articles a, an, or the. We apply the log-linear model to automatically restore missing articles based on features of the noun phrase. We first show that the model yields competitive results in article generation. Further, we describe methods to adjust the model with respect to the initial quality of the sentence. Our best results are 20.5% article error rate (insertions, deletions and substitutions) for sentences where 30% of the articles have been dropped, and 38.5% for those where 70% of the articles have been dropped.
Original language | English |
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Title of host publication | HLT-NAACL 2004 - Human Language Technology Conference of the North American Chapter of the Association for Computational Linguistics, Proceedings of the Student Research Workshop |
Publisher | Association for Computational Linguistics |
Pages | 31-36 |
DOIs | |
Publication status | Published - 2004 |
Externally published | Yes |
Event | 2004 Human Language Technology Conference of the North American Chapter of the Association for Computational Linguistics - Student Research Workshop, HLT-NAACL 2004 - Boston, United States Duration: 2 May 2004 → 7 May 2004 https://aclanthology.org/N04-2000/ |
Publication series
Name | HLT-NAACL 2004 - Human Language Technology Conference of the North American Chapter of the Association for Computational Linguistics, Proceedings of the Student Research Workshop |
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Conference
Conference | 2004 Human Language Technology Conference of the North American Chapter of the Association for Computational Linguistics - Student Research Workshop, HLT-NAACL 2004 |
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Country/Territory | United States |
City | Boston |
Period | 2/05/04 → 7/05/04 |
Internet address |