Design and implementation of an open source Greek POS Tagger and Entity Recognizer using spaCy
Abstract
This paper proposes a machine learning approach to part-of-speech tagging and named entity recognition for Greek, focusing on the extraction of morphological features and classification of tokens into a small set of classes for named entities. The architecture model that was used is introduced. The greek version of the spaCy platform was added into the source code, a feature that did not exist before our contribution, and was used for building the models. Additionally, a part of speech tagger was trained that can detect the morphology of the tokens and performs higher than the state-of-the-art results when classifying only the part of speech. For named entity recognition using spaCy, a model that extends the standard ENAMEX type (organization, location, person) was built. Certain experiments that were conducted indicate the need for flexibility in out-of-vocabulary words and there is an effort for resolving this issue. Finally, the evaluation results are discussed.
Keywords
Cite
@article{arxiv.1912.10162,
title = {Design and implementation of an open source Greek POS Tagger and Entity Recognizer using spaCy},
author = {Eleni Partalidou and Eleftherios Spyromitros-Xioufis and Stavros Doropoulos and Stavros Vologiannidis and Konstantinos I. Diamantaras},
journal= {arXiv preprint arXiv:1912.10162},
year = {2019}
}