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EnglishNeural architectures are the current state of the art in Word Sense Disambiguation (WSD). However, they make limited use of the vast amount of relational information encoded in Lexical Knowledge Bases (LKB). We present Enhanced WSD Integrating Synset Embeddings and Relations (EWISER), a neural supervised architecture that is able to tap into this wealth of knowledge by embedding information from the LKB graph within the neural architecture, and to exploit pretrained synset embeddings, enabling the network to predict synsets that are not in the training set. As a result, we set a new state of the art on almost all the evaluation settings considered, also breaking through, for the first time, the 80% ceiling on the concatenation of all the standard all-words English WSD evaluation benchmarks. On multilingual all-words WSD, we report state-of-the-art results by training on nothing but English.
Breaking Through the 80% Glass Ceiling: Raising the State of the Art in Word Sense Disambiguation by Incorporating Knowledge Graph Information / Bevilacqua, Michele; Navigli, Roberto. - (2020), pp. 2854-2864. ((Intervento presentato al convegno Annual Meeting of the Association for Computational Linguistics tenutosi a Online [10.18653/v1/2020.acl-main.255].
| Titolo: | Breaking Through the 80% Glass Ceiling: Raising the State of the Art in Word Sense Disambiguation by Incorporating Knowledge Graph Information | |
| Autori: | ||
| Data di pubblicazione: | 2020 | |
| Citazione: | Breaking Through the 80% Glass Ceiling: Raising the State of the Art in Word Sense Disambiguation by Incorporating Knowledge Graph Information / Bevilacqua, Michele; Navigli, Roberto. - (2020), pp. 2854-2864. ((Intervento presentato al convegno Annual Meeting of the Association for Computational Linguistics tenutosi a Online [10.18653/v1/2020.acl-main.255]. | |
| Handle: | http://hdl.handle.net/11573/1431881 | |
| ISBN: | 978-1-952148-25-5 | |
| Appartiene alla tipologia: | 04b Atto di convegno in volume |
File allegati a questo prodotto
| File | Note | Tipologia | Licenza | |
|---|---|---|---|---|
| Bevilacqua_Breaking-Through_2020.pdf | https://www.aclweb.org/anthology/2020.acl-main.255/ | Versione editoriale (versione pubblicata con il layout dell'editore) | Tutti i diritti riservati (All rights reserved) | Open Access Visualizza/Apri |
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