Model-based annotation of coreference
Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
Humans do not make inferences over texts, but over models of what texts are about. When annotators are asked to annotate coreferent spans of text, it is therefore a somewhat unnatural task. This paper presents an alternative in which we preprocess documents, linking entities to a knowledge base, and turn the coreference annotation task - in our case limited to pronouns - into an annotation task where annotators are asked to assign pronouns to entities. Model-based annotation is shown to lead to faster annotation and higher inter-annotator agreement, and we argue that it also opens up for an alternative approach to coreference resolution. We present two new coreference benchmark datasets, for English Wikipedia and English teacher-student dialogues, and evaluate state-of-the-art coreference resolvers on them.
Originalsprog | Engelsk |
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Titel | LREC 2020 - 12th International Conference on Language Resources and Evaluation, Conference Proceedings |
Redaktører | Nicoletta Calzolari, Frederic Bechet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Helene Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis |
Forlag | European Language Resources Association (ELRA) |
Publikationsdato | 2020 |
Sider | 74-79 |
ISBN (Elektronisk) | 9791095546344 |
Status | Udgivet - 2020 |
Begivenhed | 12th International Conference on Language Resources and Evaluation, LREC 2020 - Marseille, Frankrig Varighed: 11 maj 2020 → 16 maj 2020 |
Konference
Konference | 12th International Conference on Language Resources and Evaluation, LREC 2020 |
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Land | Frankrig |
By | Marseille |
Periode | 11/05/2020 → 16/05/2020 |
Sponsor | Amazon AWS, Bertin, Lenovo, Ontotex, Vecsys, Vocapia |
ID: 258332299