@inproceedings{nedoluzhko-etal-2026-introducing,
title = "Introducing corpora Hlava Cor and Hlava {AD}: Human Label Variation in Coreference and Discourse Relations",
author = "Nedoluzhko, Anna and
Zikanova, Sarka and
Mirovsky, Jiri and
Straka, Milan and
Hajicova, Eva",
editor = "Hinrichs, Erhard and
Nivre, Joakim and
Osenova, Petya and
Pustejovsky, James and
Zinn, Claus",
booktitle = "Proceedings of the Workshop on Structured Linguistic Data and Evaluation ({SL}i{DE})",
month = may,
year = "2026",
address = "Palma de Mallorca, Spain",
publisher = "ELRA Language Resources Association (ELRA)",
url = "https://aclanthology.org/2026.slide-1.21/",
doi = "10.63317/4qfnczvpcaxp",
pages = "237--247",
abstract = "As previous research on annotator disagreement in discourse phenomena has shown, understanding text coherence varies considerably from one individual to another. To explore this phenomenon, we created two corpora with multiple annotations of Czech texts, accompanied by annotators' explanations of their choices. The first corpus consists of 1,024 contexts annotated in parallel by three annotators. It captures differences in the identification of coreference across various text types and grammatical-semantic categories, including pronouns, full noun phrases, and anaphoric adverbials. The second corpus comprises 512 contexts, annotated in parallel by five annotators, and focuses on identifying discourse relations in attributive and non-attributive constructions. Both corpora achieve a comparable inter-annotator agreement of approximately 60{--}65{\%}. For coreference annotation, agreement tends to be lower in cases where automatic coreference resolution models disagree, suggesting that when the models disagree, the examples tend to be more difficult or ambiguous for human annotators to interpret. The annotators' comments, both for coreference and discourse relations, further reveal differences in interpretation, varying levels of confidence in text understanding, and individual reading strategies."
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%0 Conference Proceedings
%T Introducing corpora Hlava Cor and Hlava AD: Human Label Variation in Coreference and Discourse Relations
%A Nedoluzhko, Anna
%A Zikanova, Sarka
%A Mirovsky, Jiri
%A Straka, Milan
%A Hajicova, Eva
%Y Hinrichs, Erhard
%Y Nivre, Joakim
%Y Osenova, Petya
%Y Pustejovsky, James
%Y Zinn, Claus
%S Proceedings of the Workshop on Structured Linguistic Data and Evaluation (SLiDE)
%D 2026
%8 May
%I ELRA Language Resources Association (ELRA)
%C Palma de Mallorca, Spain
%F nedoluzhko-etal-2026-introducing
%X As previous research on annotator disagreement in discourse phenomena has shown, understanding text coherence varies considerably from one individual to another. To explore this phenomenon, we created two corpora with multiple annotations of Czech texts, accompanied by annotators’ explanations of their choices. The first corpus consists of 1,024 contexts annotated in parallel by three annotators. It captures differences in the identification of coreference across various text types and grammatical-semantic categories, including pronouns, full noun phrases, and anaphoric adverbials. The second corpus comprises 512 contexts, annotated in parallel by five annotators, and focuses on identifying discourse relations in attributive and non-attributive constructions. Both corpora achieve a comparable inter-annotator agreement of approximately 60–65%. For coreference annotation, agreement tends to be lower in cases where automatic coreference resolution models disagree, suggesting that when the models disagree, the examples tend to be more difficult or ambiguous for human annotators to interpret. The annotators’ comments, both for coreference and discourse relations, further reveal differences in interpretation, varying levels of confidence in text understanding, and individual reading strategies.
%R 10.63317/4qfnczvpcaxp
%U https://aclanthology.org/2026.slide-1.21/
%U https://doi.org/10.63317/4qfnczvpcaxp
%P 237-247
Markdown (Informal)
[Introducing corpora Hlava Cor and Hlava AD: Human Label Variation in Coreference and Discourse Relations](https://aclanthology.org/2026.slide-1.21/) (Nedoluzhko et al., SLiDE 2026)
ACL