A Multilingual Evaluation Dataset for Monolingual Word Sense Alignment
Sina Ahmadi, John Philip McCrae, Sanni Nimb, Fahad Khan, Monica Monachini, Bolette Pedersen, Thierry Declerck, Tanja Wissik, Andrea Bellandi, Irene Pisani, Thomas Troelsgård, Sussi Olsen, 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
Abstract
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.- Anthology ID:
- 2020.lrec-1.395
- Volume:
- Proceedings of the Twelfth Language Resources and Evaluation Conference
- Month:
- May
- Year:
- 2020
- Address:
- Marseille, France
- Editors:
- Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association
- Note:
- Pages:
- 3232–3242
- Language:
- English
- URL:
- https://aclanthology.org/2020.lrec-1.395
- DOI:
- Bibkey:
- Cite (ACL):
- Sina Ahmadi, John Philip McCrae, Sanni Nimb, Fahad Khan, Monica Monachini, Bolette Pedersen, Thierry Declerck, Tanja Wissik, Andrea Bellandi, Irene Pisani, Thomas Troelsgård, Sussi Olsen, Simon Krek, Veronika Lipp, Tamás Váradi, László Simon, András Gyorffy, Carole Tiberius, Tanneke Schoonheim, et al.. 2020. A Multilingual Evaluation Dataset for Monolingual Word Sense Alignment. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 3232–3242, Marseille, France. European Language Resources Association.
- Cite (Informal):
- A Multilingual Evaluation Dataset for Monolingual Word Sense Alignment (Ahmadi et al., LREC 2020)
- Copy Citation:
- PDF:
- https://aclanthology.org/2020.lrec-1.395.pdf
- Code
- elexis-eu/MWSA
Export citation
@inproceedings{ahmadi-etal-2020-multilingual,
title = "A Multilingual Evaluation Dataset for Monolingual Word Sense Alignment",
author = "Ahmadi, Sina and
McCrae, John Philip and
Nimb, Sanni and
Khan, Fahad and
Monachini, Monica and
Pedersen, Bolette and
Declerck, Thierry and
Wissik, Tanja and
Bellandi, Andrea and
Pisani, Irene and
Troelsg{\aa}rd, Thomas and
Olsen, Sussi and
Krek, Simon and
Lipp, Veronika and
V{\'a}radi, Tam{\'a}s and
Simon, L{\'a}szl{\'o} and
Gyorffy, Andr{\'a}s and
Tiberius, Carole and
Schoonheim, Tanneke and
Ben Moshe, Yifat and
Rudich, Maya and
Abu Ahmad, Raya and
Lonke, Dorielle and
Kovalenko, Kira and
Langemets, Margit and
Kallas, Jelena and
Dereza, Oksana and
Fransen, Theodorus and
Cillessen, David and
Lindemann, David and
Alonso, Mikel and
Salgado, Ana and
Luis Sancho, Jos{\'e} and
Ure{\~n}a-Ruiz, Rafael-J. and
Porta Zamorano, Jordi and
Simov, Kiril and
Osenova, Petya and
Kancheva, Zara and
Radev, Ivaylo and
Stankovi{\'c}, Ranka and
Perdih, Andrej and
Gabrovsek, Dejan",
editor = "Calzolari, Nicoletta and
B{\'e}chet, Fr{\'e}d{\'e}ric and
Blache, Philippe and
Choukri, Khalid and
Cieri, Christopher and
Declerck, Thierry and
Goggi, Sara and
Isahara, Hitoshi and
Maegaard, Bente and
Mariani, Joseph and
Mazo, H{\'e}l{\`e}ne and
Moreno, Asuncion and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Twelfth Language Resources and Evaluation Conference",
month = may,
year = "2020",
address = "Marseille, France",
publisher = "European Language Resources Association",
url = "https://aclanthology.org/2020.lrec-1.395",
pages = "3232--3242",
abstract = "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 \url{https://github.com/elexis-eu/MWSA}.",
language = "English",
ISBN = "979-10-95546-34-4",
}
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<abstract>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.</abstract>
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%0 Conference Proceedings %T A Multilingual Evaluation Dataset for Monolingual Word Sense Alignment %A Ahmadi, Sina %A McCrae, John Philip %A Nimb, Sanni %A Khan, Fahad %A Monachini, Monica %A Pedersen, Bolette %A Declerck, Thierry %A Wissik, Tanja %A Bellandi, Andrea %A Pisani, Irene %A Troelsgård, Thomas %A Olsen, Sussi %A Krek, Simon %A Lipp, Veronika %A Váradi, Tamás %A Simon, László %A Gyorffy, András %A Tiberius, Carole %A Schoonheim, Tanneke %A Ben Moshe, Yifat %A Rudich, Maya %A Abu Ahmad, Raya %A Lonke, Dorielle %A Kovalenko, Kira %A Langemets, Margit %A Kallas, Jelena %A Dereza, Oksana %A Fransen, Theodorus %A Cillessen, David %A Lindemann, David %A Alonso, Mikel %A Salgado, Ana %A Luis Sancho, José %A Ureña-Ruiz, Rafael-J. %A Porta Zamorano, Jordi %A Simov, Kiril %A Osenova, Petya %A Kancheva, Zara %A Radev, Ivaylo %A Stanković, Ranka %A Perdih, Andrej %A Gabrovsek, Dejan %Y Calzolari, Nicoletta %Y Béchet, Frédéric %Y Blache, Philippe %Y Choukri, Khalid %Y Cieri, Christopher %Y Declerck, Thierry %Y Goggi, Sara %Y Isahara, Hitoshi %Y Maegaard, Bente %Y Mariani, Joseph %Y Mazo, Hélène %Y Moreno, Asuncion %Y Odijk, Jan %Y Piperidis, Stelios %S Proceedings of the Twelfth Language Resources and Evaluation Conference %D 2020 %8 May %I European Language Resources Association %C Marseille, France %@ 979-10-95546-34-4 %G English %F ahmadi-etal-2020-multilingual %X 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. %U https://aclanthology.org/2020.lrec-1.395 %P 3232-3242
Markdown (Informal)
[A Multilingual Evaluation Dataset for Monolingual Word Sense Alignment](https://aclanthology.org/2020.lrec-1.395) (Ahmadi et al., LREC 2020)
- A Multilingual Evaluation Dataset for Monolingual Word Sense Alignment (Ahmadi et al., LREC 2020)
ACL
- Sina Ahmadi, John Philip McCrae, Sanni Nimb, Fahad Khan, Monica Monachini, Bolette Pedersen, Thierry Declerck, Tanja Wissik, Andrea Bellandi, Irene Pisani, Thomas Troelsgård, Sussi Olsen, Simon Krek, Veronika Lipp, Tamás Váradi, László Simon, András Gyorffy, Carole Tiberius, Tanneke Schoonheim, et al.. 2020. A Multilingual Evaluation Dataset for Monolingual Word Sense Alignment. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 3232–3242, Marseille, France. European Language Resources Association.