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arXiv · 1711.06196

Addressing Cross-Lingual Word Sense Disambiguation on Low-Density Languages: Application to Persian

Navid Rekabsaz·Mihai Lupu·Allan Hanbury·Andres Duque
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Abstract

We explore the use of unsupervised methods in Cross-Lingual Word Sense Disambiguation (CL-WSD) with the application of English to Persian. Our proposed approach targets the languages with scarce resources (low-density) by exploiting word embedding and semantic similarity of the words in context. We evaluate the approach on a recent evaluation benchmark and compare it with the state-of-the-art unsupervised system (CO-Graph). The results show that our approach outperforms both the standard baseline and the CO-Graph system in both of the task evaluation metrics (Out-Of-Five and Best result).

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Navid Rekabsaz, Mihai Lupu, Allan Hanbury, Andres Duque. 2017-11-16. Addressing Cross-Lingual Word Sense Disambiguation on Low-Density Languages: Application to Persian. https://arxiv.org/abs/1711.06196

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