The Natural Language Processing (NLP) community has recently experienced a growing interest in Semantic Role Labeling (SRL). The increased availability of annotated resources enables the development of statistical approaches specifically for SRL. This holds potential impact in NLP applications. We examine and reproduce the Marcheggiani’s system and its individual components, including its annotated resources, parser, classification system, the features used and the results obtained by the system. Then, we explore different solutions in order to achieve better results by approaching to Verb-Sense Disambiguation (VSD). VSD is a sub-problem of the Word Sense Disambiguation (WSD) problem, that tries to identify in which sense a polysemic word is used in a given sentence. Thus a sense inventory for each word (or lemma)
must be used. Finally, we also assess the challenges in SRL and identify the opportunities for useful further research in future.

Evento: CLiC-it 2019 – Sixth Italian Conference on Computational Linguistics , 2019 – Bari (Italy)
Data: 2019
Autori: Domenico Alfano, Roberto Abbruzzese, Donato Cappetta