Yu, Juntao and Paun, Silviu and Camilleri, Maris and Carretero Garcia, Paloma and Chamberlain, Jon and Kruschwitz, Udo and Poesio, Massimo (2023) Aggregating Crowdsourced and Automatic Judgments to Scale Up a Corpus of Anaphoric Reference for Fiction and Wikipedia Texts. In: The 17th Conference of the European Chapter of the Association for Computational Linguistics, 2023-05-02 - 2023-05-06, Dubrovnik, Croatia.
Yu, Juntao and Paun, Silviu and Camilleri, Maris and Carretero Garcia, Paloma and Chamberlain, Jon and Kruschwitz, Udo and Poesio, Massimo (2023) Aggregating Crowdsourced and Automatic Judgments to Scale Up a Corpus of Anaphoric Reference for Fiction and Wikipedia Texts. In: The 17th Conference of the European Chapter of the Association for Computational Linguistics, 2023-05-02 - 2023-05-06, Dubrovnik, Croatia.
Yu, Juntao and Paun, Silviu and Camilleri, Maris and Carretero Garcia, Paloma and Chamberlain, Jon and Kruschwitz, Udo and Poesio, Massimo (2023) Aggregating Crowdsourced and Automatic Judgments to Scale Up a Corpus of Anaphoric Reference for Fiction and Wikipedia Texts. In: The 17th Conference of the European Chapter of the Association for Computational Linguistics, 2023-05-02 - 2023-05-06, Dubrovnik, Croatia.
Abstract
Although several datasets annotated for anaphoric reference / coreference exist, even the largest such datasets have limitations in term of size, range of domains, coverage of anaphoric phenomena, and size of documents included. Yet, the approaches proposed to scale up anaphoric annotation haven’t so far resulted in datasets overcoming these limitations. In this paper, we introduce a new release of a corpus for anaphoric reference labelled via a game-with-a-purpose. This new release is comparable in size to the largest existing corpora for anaphoric reference due in part to substantial activity by the players, in part thanks to the use of a new resolve-and-aggregate paradigm to ‘complete’ markable annotations through the combination of an anaphoric resolver and an aggregation method for anaphoric reference. The proposed method could be adopted to greatly speed up annotation time in other projects involving games-with-a-purpose. In addition, the corpus covers genres for which no comparable size datasets exist (Fiction and Wikipedia); it covers singletons and non-referring expressions; and it includes a substantial number of long documents ( 2K in length).
Item Type: | Conference or Workshop Item (Paper) |
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Divisions: | Faculty of Science and Health Faculty of Science and Health > Computer Science and Electronic Engineering, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 08 Feb 2024 11:08 |
Last Modified: | 30 Oct 2024 20:04 |
URI: | http://repository.essex.ac.uk/id/eprint/34845 |
Available files
Filename: 305_Paper.pdf
Licence: Creative Commons: Attribution 4.0