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        <title>A Discriminative Analysis of Fine-Grained Semantic Relations including Presupposition: Annotation and Classification</title>
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    <abstract>In contrast to classical lexical semantic relations between verbs, such as antonymy, synonymy or hypernymy, presupposition is a lexically triggered semantic relation that is not well covered in existing lexical resources. It is also understudied in the field of corpus-based methods of learning semantic relations. Yet, presupposition is very important for semantic and discourse analysis tasks, given the implicit information that it conveys. In this paper we present a corpus-based method for acquiring presupposition-triggering verbs along with verbal relata that express their presupposed meaning. We approach this difficult task using a discriminative classification method that jointly determines and distinguishes a broader set of inferential semantic relations between verbs. The present paper focuses on important methodological aspects of our work: (i) a discriminative analysis of the semantic properties of the chosen set of relations, (ii) the selection of features for corpus-based classification and (iii) design decisions for the manual annotation of fine-grained semantic relations between verbs. (iv) We present the results of a practical annotation effort leading to a gold standard resource for our relation inventory, and (v) we report results for automatic classification of our target set of fine-grained semantic relations, including presupposition. We achieve a classification performance of 55% F1-score, a 100% improvement over a best-feature baseline.</abstract>
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%0 Journal Article
%T A Discriminative Analysis of Fine-Grained Semantic Relations including Presupposition: Annotation and Classification
%A Tremper, Galina
%A Frank, Anette
%J Dialogue & Discourse
%D 2013
%8 July
%V 4
%I University of Bielefeld
%C Bielefeld, Germany
%F tremper-frank-2013-discriminative
%X In contrast to classical lexical semantic relations between verbs, such as antonymy, synonymy or hypernymy, presupposition is a lexically triggered semantic relation that is not well covered in existing lexical resources. It is also understudied in the field of corpus-based methods of learning semantic relations. Yet, presupposition is very important for semantic and discourse analysis tasks, given the implicit information that it conveys. In this paper we present a corpus-based method for acquiring presupposition-triggering verbs along with verbal relata that express their presupposed meaning. We approach this difficult task using a discriminative classification method that jointly determines and distinguishes a broader set of inferential semantic relations between verbs. The present paper focuses on important methodological aspects of our work: (i) a discriminative analysis of the semantic properties of the chosen set of relations, (ii) the selection of features for corpus-based classification and (iii) design decisions for the manual annotation of fine-grained semantic relations between verbs. (iv) We present the results of a practical annotation effort leading to a gold standard resource for our relation inventory, and (v) we report results for automatic classification of our target set of fine-grained semantic relations, including presupposition. We achieve a classification performance of 55% F1-score, a 100% improvement over a best-feature baseline.
%R 10.5087/dad.2013.212
%U https://aclanthology.org/2013.dnd-4.4/
%U https://doi.org/10.5087/dad.2013.212
%P 282-322

Markdown (Informal)

[A Discriminative Analysis of Fine-Grained Semantic Relations including Presupposition: Annotation and Classification](https://aclanthology.org/2013.dnd-4.4/) (Tremper & Frank, DND 2013)

• A Discriminative Analysis of Fine-Grained Semantic Relations including Presupposition: Annotation and Classification (Tremper & Frank, DND 2013)

ACL

• Galina Tremper and Anette Frank. 2013. A Discriminative Analysis of Fine-Grained Semantic Relations including Presupposition: Annotation and Classification. Dialogue & Discourse, 4:282–322.