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|Title:||Automatic acquisition of Named Entities for Rule-Based Machine Translation|
|Others:||International Workshop on Free/Open-Source Rule-Based Machine Translation (2nd : 2011 : Barcelona)|
|Publisher:||Universitat Oberta de Catalunya|
|Citation:||Toral, Antonio; Way, Andy (2011, January). "Automatic acquisition of Named Entities for Rule-Based Machine Translation". Proceedings of the Second International Workshop on Free/Open-Source Rule-Based Machine Translation (2011: Barcelona). <http://hdl.handle.net/10609/5644>|
|Abstract:||This paper proposes to enrich RBMT dictionaries with Named Entities (NEs) automatically acquired from Wikipedia. The method is applied to the Apertium English-Spanish system and its performance compared to that of Apertium with and without handtagged NEs. The system with automatic NEs outperforms the one without NEs, while results vary when compared to a system with handtagged NEs (results are comparable for Spanish to English but slightly worst for English to Spanish). Apart from that, adding automatic NEs contributes to decreasing the amount of unknown terms by more than 10%.|
|Appears in Collections:||Second International Workshop on Free/Open-Source Rule-Based Machine Translation, (Barcelona, 20 January 2011)|
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