@inproceedings{rehbein-ruppenhofer-2020-new,
title = "A New Resource for {G}erman Causal Language",
author = "Rehbein, Ines and
Ruppenhofer, Josef",
booktitle = "Proceedings of the 12th Language Resources and Evaluation Conference",
month = may,
year = "2020",
address = "Marseille, France",
publisher = "European Language Resources Association",
url = "https://aclanthology.org/2020.lrec-1.731",
pages = "5968--5977",
abstract = "We present a new resource for German causal language, with annotations in context for verbs, nouns and prepositions. Our dataset includes 4,390 annotated instances for more than 150 different triggers. The annotation scheme distinguishes three different types of causal events (CONSEQUENCE , MOTIVATION, PURPOSE). We also provide annotations for semantic roles, i.e. of the cause and effect for the causal event as well as the actor and affected party, if present. In the paper, we present inter-annotator agreement scores for our dataset and discuss problems for annotating causal language. Finally, we present experiments where we frame causal annotation as a sequence labelling problem and report baseline results for the prediciton of causal arguments and for predicting different types of causation.",
language = "English",
ISBN = "979-10-95546-34-4",
}
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<abstract>We present a new resource for German causal language, with annotations in context for verbs, nouns and prepositions. Our dataset includes 4,390 annotated instances for more than 150 different triggers. The annotation scheme distinguishes three different types of causal events (CONSEQUENCE , MOTIVATION, PURPOSE). We also provide annotations for semantic roles, i.e. of the cause and effect for the causal event as well as the actor and affected party, if present. In the paper, we present inter-annotator agreement scores for our dataset and discuss problems for annotating causal language. Finally, we present experiments where we frame causal annotation as a sequence labelling problem and report baseline results for the prediciton of causal arguments and for predicting different types of causation.</abstract>
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%0 Conference Proceedings
%T A New Resource for German Causal Language
%A Rehbein, Ines
%A Ruppenhofer, Josef
%S Proceedings of the 12th 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 rehbein-ruppenhofer-2020-new
%X We present a new resource for German causal language, with annotations in context for verbs, nouns and prepositions. Our dataset includes 4,390 annotated instances for more than 150 different triggers. The annotation scheme distinguishes three different types of causal events (CONSEQUENCE , MOTIVATION, PURPOSE). We also provide annotations for semantic roles, i.e. of the cause and effect for the causal event as well as the actor and affected party, if present. In the paper, we present inter-annotator agreement scores for our dataset and discuss problems for annotating causal language. Finally, we present experiments where we frame causal annotation as a sequence labelling problem and report baseline results for the prediciton of causal arguments and for predicting different types of causation.
%U https://aclanthology.org/2020.lrec-1.731
%P 5968-5977
Markdown (Informal)
[A New Resource for German Causal Language](https://aclanthology.org/2020.lrec-1.731) (Rehbein & Ruppenhofer, LREC 2020)
ACL
- Ines Rehbein and Josef Ruppenhofer. 2020. A New Resource for German Causal Language. In Proceedings of the 12th Language Resources and Evaluation Conference, pages 5968–5977, Marseille, France. European Language Resources Association.