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Found 5 papers, 3 papers with code
ConSeC: Word Sense Disambiguation as Continuous Sense Comprehension
Supervised systems have nowadays become the standard recipe for Word Sense Disambiguation (WSD), with Transformer-based language models as their primary ingredient.
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Word Sense Disambiguation
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ExtEnD: Extractive Entity Disambiguation
Local models for Entity Disambiguation (ED) have today become extremely powerful, in most part thanks to the advent of large pre-trained language models.
Word Sense Linking: Disambiguating Outside the Sandbox
In this work, we present a new task called Word Sense Linking (WSL) where, given an input text and a reference sense inventory, systems have to both identify which spans to disambiguate and then link them to their most suitable meaning. We put forward a transformer-based architecture for the task and thoroughly evaluate both its performance and those of state-of-the-art WSD systems scaled to WSL, iteratively relaxing the assumptions of WSD.
Entity Disambiguation with Entity Definitions
Local models have recently attained astounding performances in Entity Disambiguation (ED), with generative and extractive formulations being the most promising research directions.
SGL: Speaking the Graph Languages of Semantic Parsing via Multilingual Translation
Graph-based semantic parsing aims to represent textual meaning through directed graphs.
