@article{marasovic-etal-2016-modal,
title = "Modal Sense Classification At Large: Paraphrase-Driven Sense Projection, Semantically Enriched Classification Models and Cross-Genre Evaluations",
author = "Marasovi{\'c}, Ana and
Zhou, Mengfei and
Palmer, Alexis and
Frank, Anette",
journal = "Linguistic Issues in Language Technology",
volume = "14",
month = "sept",
year = "2016",
publisher = "CSLI Publications",
url = "https://aclanthology.org/2016.lilt-14.3",
abstract = "Modal verbs have different interpretations depending on their context. Their sense categories {--} epistemic, deontic and dynamic {--} provide important dimensions of meaning for the interpretation of discourse. Previous work on modal sense classification achieved relatively high performance using shallow lexical and syntactic features drawn from small-size annotated corpora. Due to the restricted empirical basis, it is difficult to assess the particular difficulties of modal sense classification and the generalization capacity of the proposed models. In this work we create large-scale, high-quality annotated corpora for modal sense classification using an automatic paraphrase-driven projection approach. Using the acquired corpora, we investigate the modal sense classification task from different perspectives.",
}
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<abstract>Modal verbs have different interpretations depending on their context. Their sense categories – epistemic, deontic and dynamic – provide important dimensions of meaning for the interpretation of discourse. Previous work on modal sense classification achieved relatively high performance using shallow lexical and syntactic features drawn from small-size annotated corpora. Due to the restricted empirical basis, it is difficult to assess the particular difficulties of modal sense classification and the generalization capacity of the proposed models. In this work we create large-scale, high-quality annotated corpora for modal sense classification using an automatic paraphrase-driven projection approach. Using the acquired corpora, we investigate the modal sense classification task from different perspectives.</abstract>
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%0 Journal Article
%T Modal Sense Classification At Large: Paraphrase-Driven Sense Projection, Semantically Enriched Classification Models and Cross-Genre Evaluations
%A Marasović, Ana
%A Zhou, Mengfei
%A Palmer, Alexis
%A Frank, Anette
%J Linguistic Issues in Language Technology
%D 2016
%8 sept
%V 14
%I CSLI Publications
%F marasovic-etal-2016-modal
%X Modal verbs have different interpretations depending on their context. Their sense categories – epistemic, deontic and dynamic – provide important dimensions of meaning for the interpretation of discourse. Previous work on modal sense classification achieved relatively high performance using shallow lexical and syntactic features drawn from small-size annotated corpora. Due to the restricted empirical basis, it is difficult to assess the particular difficulties of modal sense classification and the generalization capacity of the proposed models. In this work we create large-scale, high-quality annotated corpora for modal sense classification using an automatic paraphrase-driven projection approach. Using the acquired corpora, we investigate the modal sense classification task from different perspectives.
%U https://aclanthology.org/2016.lilt-14.3
Markdown (Informal)
[Modal Sense Classification At Large: Paraphrase-Driven Sense Projection, Semantically Enriched Classification Models and Cross-Genre Evaluations](https://aclanthology.org/2016.lilt-14.3) (Marasović et al., LILT 2016)
ACL