| Challenge: | Existing datasets for predicate-argument relationships are lacking highly skilled and trained annotators. |
| Approach: | They propose a crowdsourcing scheme to generate question-answer pairs that represent predicate-argument relationships in sentences as a set of question-announcer pairs. |
| Outcome: | The proposed model covers the vast majority of predicate-argument relationships in existing datasets along with many previously under-resourced ones, including implicit arguments and relations. |
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| Challenge: | Discourse relations describe how two propositions relate to one another . annotating discourse relations requires expert annotators . |
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QuASE: Question-Answer Driven Sentence Encoding (2020.acl-main)
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Ayal Klein, Jonathan Mamou, Valentina Pyatkin, Daniela Stepanov, Hangfeng He, Dan Roth, Luke Zettlemoyer, Ido Dagan
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| Challenge: | Current approaches to question answering rely on pre-trained language models like RoBERTa. |
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| Challenge: | Mars? - PragmatiCQA |
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| Challenge: | This tutorial reviews the design of common meaning representations and SoTA models for predicting meaning representation models. |
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Meaning Representations for Natural Languages: Design, Models and Applications (2024.lrec-tutorials)
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| Challenge: | a tutorial reviews the design of common meaning representations and SoTA models for predicting meaning representation. |
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