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Open AccessFeature PaperArticle

Event Extraction and Representation: A Case Study for the Portuguese Language

Informatics Department, University of Évora, 7000-671 Évora, Portugal
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Information 2019, 10(6), 205; https://doi.org/10.3390/info10060205
Received: 11 May 2019 / Revised: 4 June 2019 / Accepted: 5 June 2019 / Published: 8 June 2019
(This article belongs to the Special Issue Natural Language Processing and Text Mining)
Text information extraction is an important natural language processing (NLP) task, which aims to automatically identify, extract, and represent information from text. In this context, event extraction plays a relevant role, allowing actions, agents, objects, places, and time periods to be identified and represented. The extracted information can be represented by specialized ontologies, supporting knowledge-based reasoning and inference processes. In this work, we will describe, in detail, our proposal for event extraction from Portuguese documents. The proposed approach is based on a pipeline of specialized natural language processing tools; namely, a part-of-speech tagger, a named entities recognizer, a dependency parser, semantic role labeling, and a knowledge extraction module. The architecture is language-independent, but its modules are language-dependent and can be built using adequate AI (i.e., rule-based or machine learning) methodologies. The developed system was evaluated with a corpus of Portuguese texts and the obtained results are presented and analysed. The current limitations and future work are discussed in detail. View Full-Text
Keywords: natural language processing; information extraction; text mining; events; ontologies population natural language processing; information extraction; text mining; events; ontologies population
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Quaresma, P.; Nogueira, V.B.; Raiyani, K.; Bayot, R. Event Extraction and Representation: A Case Study for the Portuguese Language. Information 2019, 10, 205.

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