Abstract
In this work we present a new framework for the analysis of Italian texts that could help linguists to perform rapid text analysis. The framework, that performs both statistical and rule-based analysis, is called LG-Starship. The idea is to built a modular software that includes the basic algorithms to perform different kinds of analysis. The framework will include a Preprocessing Module a POS Tagging and Lemmatization module, a Statistic Module, a Semantic Module based on Distributional Analysis algorithms, and a Syntactic Module, which analyses syntax structures of a selected sentence and tags the verbs and its arguments with semantic labels. The objective of the Framework is to build an “all-in-one” platform for NLP which allows any kind of users to perform basic and advanced text analysis.
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Elia, A., Maisto, A., Martorelli, G., Pelosi, S., Vitale, P. (2020). Textual Statistics and Named Entity Recognition Applied to Game of Thrones Novels. In: Barolli, L., Amato, F., Moscato, F., Enokido, T., Takizawa, M. (eds) Web, Artificial Intelligence and Network Applications. WAINA 2020. Advances in Intelligent Systems and Computing, vol 1150. Springer, Cham. https://doi.org/10.1007/978-3-030-44038-1_20
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