A Multilingual Evaluation Dataset for Monolingual Word Sense Alignment

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

  • Sina Ahmadi
  • John McCrae
  • Sanni Nimb
  • Fahad Khan
  • Monica Monachini
  • Thierry Declerck
  • Tanja Wissik
  • Andrea Bellandi
  • Irene Pisani
  • Thomas Troelsgård
  • Simon Krek
  • Veronika Lipp
  • Tamás Váradi
  • László Simon
  • András Gyorffy
  • Carole Tiberius
  • Tanneke Schoonheim
  • Yifat Ben Moshe
  • Maya Rudich
  • Raya Abu Ahmad
  • Dorielle Lonke
  • Kira Kovalenko
  • Margit Langemets
  • Jelena Kallas
  • Oksana Dereza
  • Theodorus Fransen
  • David Cillessen
  • David Lindemann
  • Mikel Alonso
  • Ana Salgado
  • José Luis Sancho
  • Rafael-J Ureña-Ruiz
  • Jordi Porta Zamorano
  • Kiril Simov
  • Petya Osenova
  • Zara Kancheva
  • Ivaylo Radev
  • Ranka Stanković
  • Andrej Perdih
  • Dejan Gabrovsek
Aligning senses across resources and languages is a challenging task with beneficial applications in the field of natural language processing and electronic lexicography. In this paper, we describe our efforts in manually aligning monolingual dictionaries. The alignment is
carried out at sense-level for various resources in 15 languages. Moreover, senses are annotated with possible semantic relationships such
as broadness, narrowness, relatedness, and equivalence. In comparison to previous datasets for this task, this dataset covers a wide range
of languages and resources and focuses on the more challenging task of linking general-purpose language. We believe that our data will
pave the way for further advances in alignment and evaluation of word senses by creating new solutions, particularly those notoriously
requiring data such as neural networks. Our resources are publicly available at https://github.com/elexis-eu/MWSA.
OriginalsprogEngelsk
TitelProceedings of the 12th Language Resources and Evaluation Conference
Antal sider10
Udgivelses stedMarseille, France
ForlagEuropean Language Resources Association
Publikationsdato2020
Sider3232-3242
ISBN (Elektronisk)979-10-95546-34-4
StatusUdgivet - 2020

ID: 241583424