Generationary or: “How We Went beyond Sense Inventories and Learnedto Gloss”

Roberto Navigli


Abstract
In this talk I present Generationary, an approach that goes beyond the mainstream assumption that word senses can be represented as discrete items of a predefined inventory, and put forward a unified model which produces contextualized definitions for arbitrary lexical items, from words to phrases and even sentences. Generationary employs a novel span-based encoding scheme to fine-tune an English pre-trained Encoder-Decoder system and generate new definitions. Our model outperforms previous approaches in the generative task of Definition Modeling in many settings, but it also matches or surpasses the state of the art in discriminative tasks such as Word Sense Disambiguation and Word-in-Context. Finally, we show that Generationary benefits from training on definitions from multiple inventories, with strong gains across benchmarks, including a novel dataset of definitions for free adjective-noun phrases.
Anthology ID:
2020.mwe-1.9
Volume:
Proceedings of the Joint Workshop on Multiword Expressions and Electronic Lexicons
Month:
December
Year:
2020
Address:
online
Venues:
COLING | MWE
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
73
Language:
URL:
https://www.aclweb.org/anthology/2020.mwe-1.9
DOI:
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PDF:
http://aclanthology.lst.uni-saarland.de/2020.mwe-1.9.pdf