@inproceedings{yu-etal-2024-ad,
title = "Ad Hoc Compounds for Stance Detection",
author = "Yu, Qi and
Schlotterbeck, Fabian and
Wang, Hening and
Reichmann, Naomi and
Stolterfoht, Britta and
Eckardt, Regine and
Butt, Miriam",
editor = {Bhatia, Archna and
Bouma, Gosse and
Do{\u{g}}ru{\"o}z, A. Seza and
Evang, Kilian and
Garcia, Marcos and
Giouli, Voula and
Han, Lifeng and
Nivre, Joakim and
Rademaker, Alexandre},
booktitle = "Proceedings of the Joint Workshop on Multiword Expressions and Universal Dependencies (MWE-UD) @ LREC-COLING 2024",
month = may,
year = "2024",
address = "Torino, Italia",
publisher = "ELRA and ICCL",
url = "https://aclanthology.org/2024.mwe-1.27",
pages = "231--242",
abstract = "In this paper we focus on a subclass of multi-word expressions, namely compound formation in German. The automatic detection of compounds is a known problem and we argue that its resolution should be given more urgency in light of a new role we uncovered with respect to ad hoc compound formation: the systematic expression of attitudinal meaning and its potential importance for the down-stream NLP task of stance detection. We demonstrate that ad hoc compounds in German indeed systematically express attitudinal meaning by adducing corpus linguistic and psycholinguistic experimental data. However, an investigation of state-of-the-art dependency parsers and Universal Dependency treebanks shows that German compounds are parsed and annotated very unevenly, so that currently one cannot reliably identify or access ad hoc compounds with attitudinal meaning in texts. Moreover, we report initial experiments with large language models underlining the challenges in capturing attitudinal meanings conveyed by ad hoc compounds. We consequently suggest a systematized way of annotating (and thereby also parsing) ad hoc compounds that is based on positive experiences from within the multilingual ParGram grammar development effort.",
}
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<abstract>In this paper we focus on a subclass of multi-word expressions, namely compound formation in German. The automatic detection of compounds is a known problem and we argue that its resolution should be given more urgency in light of a new role we uncovered with respect to ad hoc compound formation: the systematic expression of attitudinal meaning and its potential importance for the down-stream NLP task of stance detection. We demonstrate that ad hoc compounds in German indeed systematically express attitudinal meaning by adducing corpus linguistic and psycholinguistic experimental data. However, an investigation of state-of-the-art dependency parsers and Universal Dependency treebanks shows that German compounds are parsed and annotated very unevenly, so that currently one cannot reliably identify or access ad hoc compounds with attitudinal meaning in texts. Moreover, we report initial experiments with large language models underlining the challenges in capturing attitudinal meanings conveyed by ad hoc compounds. We consequently suggest a systematized way of annotating (and thereby also parsing) ad hoc compounds that is based on positive experiences from within the multilingual ParGram grammar development effort.</abstract>
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%0 Conference Proceedings
%T Ad Hoc Compounds for Stance Detection
%A Yu, Qi
%A Schlotterbeck, Fabian
%A Wang, Hening
%A Reichmann, Naomi
%A Stolterfoht, Britta
%A Eckardt, Regine
%A Butt, Miriam
%Y Bhatia, Archna
%Y Bouma, Gosse
%Y Doğruöz, A. Seza
%Y Evang, Kilian
%Y Garcia, Marcos
%Y Giouli, Voula
%Y Han, Lifeng
%Y Nivre, Joakim
%Y Rademaker, Alexandre
%S Proceedings of the Joint Workshop on Multiword Expressions and Universal Dependencies (MWE-UD) @ LREC-COLING 2024
%D 2024
%8 May
%I ELRA and ICCL
%C Torino, Italia
%F yu-etal-2024-ad
%X In this paper we focus on a subclass of multi-word expressions, namely compound formation in German. The automatic detection of compounds is a known problem and we argue that its resolution should be given more urgency in light of a new role we uncovered with respect to ad hoc compound formation: the systematic expression of attitudinal meaning and its potential importance for the down-stream NLP task of stance detection. We demonstrate that ad hoc compounds in German indeed systematically express attitudinal meaning by adducing corpus linguistic and psycholinguistic experimental data. However, an investigation of state-of-the-art dependency parsers and Universal Dependency treebanks shows that German compounds are parsed and annotated very unevenly, so that currently one cannot reliably identify or access ad hoc compounds with attitudinal meaning in texts. Moreover, we report initial experiments with large language models underlining the challenges in capturing attitudinal meanings conveyed by ad hoc compounds. We consequently suggest a systematized way of annotating (and thereby also parsing) ad hoc compounds that is based on positive experiences from within the multilingual ParGram grammar development effort.
%U https://aclanthology.org/2024.mwe-1.27
%P 231-242
Markdown (Informal)
[Ad Hoc Compounds for Stance Detection](https://aclanthology.org/2024.mwe-1.27) (Yu et al., MWE-UDW-WS 2024)
ACL
- Qi Yu, Fabian Schlotterbeck, Hening Wang, Naomi Reichmann, Britta Stolterfoht, Regine Eckardt, and Miriam Butt. 2024. Ad Hoc Compounds for Stance Detection. In Proceedings of the Joint Workshop on Multiword Expressions and Universal Dependencies (MWE-UD) @ LREC-COLING 2024, pages 231–242, Torino, Italia. ELRA and ICCL.