Abstract
In this paper, a machine learning based Relation Extraction experiments for data from Arabic language are presented. There were 6 Types of relations involved in the experiments and 18 Sub-Types. By this work, a baseline for statistical Relation Extraction for Arabic is being created, with .85 acc., testing on 10-folds for the ACE 2005 Multilingual Training Data V6.0. Several factors contributed to the enhancements of accuracy for the testing data, especially the morphological and POS information using MaxEnt classifiers.
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Alotayq, A. (2013). Extracting Relations between Arabic Named Entities. In: Habernal, I., Matoušek, V. (eds) Text, Speech, and Dialogue. TSD 2013. Lecture Notes in Computer Science(), vol 8082. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40585-3_34
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DOI: https://doi.org/10.1007/978-3-642-40585-3_34
Publisher Name: Springer, Berlin, Heidelberg
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