May is the month for exams at the Norwegian college where I work. There is a special
atmosphere in the air as students gather in groups to discuss the various subjects they have …

In this paper we discuss a persistent problem arising from polysemy: namely the difficulty of
finding consistent criteria for making fine-grained sense distinctions, either manually or …

Most words have multiple meanings, but there are foundationally distinct accounts for this.
Categorical theories posit that humans maintain discrete entries for distinct word meanings …

Recent discussions of annotator agreement have mostly centered around its calculation and
interpretation, and the correct choice of indices. Although these discussions are important …

Human languages evolve to make communication more efficient. But efficiency creates trade-
offs: what is efficient for speakers is not always efficient for comprehenders. How do …

Word sense disambiguation (WSD) is an old and important task in computational linguistics
that still remains challenging, to machines as well as to human annotators. Recently there …

Annotated data is prerequisite for many NLP applications. Acquiring large-scale annotated
corpora is a major bottleneck, requiring significant time and resources. Recent work has …

The vast majority of work on word senses has relied on predefined sense inventories and an
annotation schema where each word instance is tagged with the best fitting sense. This …

Word senses Page 50 Adam Kilgarriff Lexical Computing Ltd. and University of Sussex The
trouble with word sense disambiguation is word senses. There are no decisive ways of …

High-quality lexical resources are needed to both train and evaluate Word Sense
Disambiguation (WSD) systems. The problem of ambiguity persists even in limited domains …