Word Sense Linking: Disambiguating Outside the Sandbox
Authors: name: Andrei Stefan Bejgu, name: Edoardo Barba, name: Luigi Procopio, name: Alberte Fernández-Castro, name: Roberto Navigli

Word Sense Disambiguation (WSD) is the task of associating a word in a given
context with its most suitable meaning among a set of possible candidates.
While the task has recently witnessed renewed interest, with systems achieving
performances above the estimated inter-annotator agreement, at the time of
writing it still struggles to find downstream applications. We argue that one
of the reasons behind this is the difficulty of applying WSD to plain text.
Indeed, in the standard formulation, models work under the assumptions that a)
all the spans to disambiguate have already been identified, and b) all the
possible candidate senses of each span are provided, both of which are
requirements that are far from trivial. 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. We hope that our work will foster
easier integration of lexical semantics into downstream applications.