UMUCorpusClassifier: Compilation and evaluation of linguistic corpus for Natural Language Processing tasks

José Antonio García-Díaz, Ángela Almela, Gema Alcaraz-Mármol, Rafael Valencia-García


The development of an annotated corpus is a very time-consuming task. Although some researchers have proposed the automatic annotation of a corpus based on ad-hoc heuristics, valid hypotheses cannot always be made. Even when the annotation process is performed by human annotators, the quality of the corpus is heavily in uenced by disagreements between annotators or with themselves. Therefore, the lack of supervision of the annotation process can lead to poor quality corpus. In this work, we propose a demonstration of UMUCorpusClassifier, a NLP tool for aid researches for compiling corpus as well as coordinating and supervising the annotation process. This tool eases the daily supervision process and permits to detect deviations and inconsistencies during early stages of the annotation process.

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