Persian Wordnet Construction using Supervised Learning

Zahra Mousavi; Heshaam Faili

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arXiv · 1704.03223

Persian Wordnet Construction using Supervised Learning

Zahra Mousavi·Heshaam Faili

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Abstract

This paper presents an automated supervised method for Persian wordnet construction. Using a Persian corpus and a bi-lingual dictionary, the initial links between Persian words and Princeton WordNet synsets have been generated. These links will be discriminated later as correct or incorrect by employing seven features in a trained classification system. The whole method is just a classification system, which has been trained on a train set containing FarsNet as a set of correct instances. State of the art results on the automatically derived Persian wordnet is achieved. The resulted wordnet with a precision of 91.18% includes more than 16,000 words and 22,000 synsets.

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Zahra Mousavi, Heshaam Faili. 2017-04-11. Persian Wordnet Construction using Supervised Learning. https://arxiv.org/abs/1704.03223

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