Abstract
Despite considerable research on the topic of Arabic Named Entity Recognition (NER), almost all efforts focus on a traditional set of semantic classes, features and token representations. In this work, we advance previous research in a systematic manner and devise a novel method to represent these features, relying on a dependency-based structure to capture further evidence within the sentence. Moreover, the work also describes an evaluation of the method involving the capture of global features and employing the clustering of unannotated textual data. To meet this set of goals, we conducted a series of evaluations to evaluate different aspects that demonstrate great improvement when compared with the baseline model.
Original language | English |
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Title of host publication | COLING 2014 - 25th International Conference on Computational Linguistics, Proceedings of COLING 2014 |
Subtitle of host publication | Technical Papers |
Publisher | Association for Computational Linguistics, ACL |
Pages | 984-995 |
Number of pages | 12 |
ISBN (Electronic) | 9781941643266 |
Publication status | Published - 1 Jan 2014 |
Event | 25th International Conference on Computational Linguistics, COLING 2014 - Dublin, Ireland Duration: 23 Aug 2014 → 29 Aug 2014 |
Conference
Conference | 25th International Conference on Computational Linguistics, COLING 2014 |
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Country/Territory | Ireland |
City | Dublin |
Period | 23/08/14 → 29/08/14 |
ASJC Scopus subject areas
- Language and Linguistics
- Linguistics and Language