Aprendizaje automático para el reconocimiento temporal multilingüe basado en TiMBL

1. Puchol Blasco, Marcel
2. Saquete Boró, Estela
3. Martínez Barco, Patricio

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More publications in: Procesamiento del lenguaje natural

Abstract

This paper presents a Machine Learning-based system for temporal expression recognition. The system uses the TiMBL application, which is a memory-based machine learning system. The portability of the system to other new languages has a very low cost, because it does not need any dependent language resource (only requires a tokenizer and a POS tagger, although the lack in POS tagger does not have enough repercussions on the final system results). This systems has been evaluated on three different languages: English, Spanish and Italian. The evaluation results are quite successful for corpus having a lot of examples; however it obtains very poor results with corpus that have only a few examples.

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