Word embeddings are real-valued word representations able to capture lexical semantics
and trained on natural language corpora. Models proposing these representations have …

The field of natural language processing (NLP) is contemporaneous with computers.
Machine translation systems were developed as early as the 1950s, and the widespread …

Abstract The Word-in-Context corpus, which forms part of the SuperGLUE benchmark
dataset, focuses on a specific sense disambiguation task: it has to be decided whether two …

For disaster preparedness, a key aspect of the work is the identification, ahead of time, of the
vocabulary of emergency messages. Here we describe how static repositories of traditional …

How do the relations used in semantic networks appear in (static) word embeddings? This
dissertation is organized around this question. In other words, how can the cognitive …

We analyze whether different sense vectors of the same word form in multi-sense word
embeddings correspond to different concepts. On the more technical side of embedding …

Az EFNILEX projekt azt szándékozott felderíteni, hogy a gépi fordítás eszközei hogyan
járulnak hozzá szótárak előállításához „közepes” európai nyelveken, vagyis az EU …

The field of natural language processing (NLP) is contemporaneous with computers.
Machine translation systems were developed as early as the 1950s, and the widespread …

We analyze whether different sense vectors of the same word form in multi-sense word
embeddings correspond to different concepts. On the more technical side of embedding …

Az elmúlt harminc év nyelvészetét a „racionalista”(szabály-alapú, szimbólumkezelő) és az
„empirista”(statisztikai alapú, gépi tanulásos) nyelvészeti modellek harca jellemezte. Míg a …