Ayal Klein, Jonathan Mamou, Valentina Pyatkin, Daniela Stepanov, Hangfeng He, Dan Roth, Luke Zettlemoyer, Ido Dagan
| Challenge: | Traditionally, SRL annotations focus on verbal predicates, but other types of predicate are frequent in natural language. |
| Approach: | They propose a semantic scheme for capturing predicate-argument relations for nominalizations, termed QANom, using crowdsourcing and QA-driven annotations. |
| Outcome: | The proposed scheme outperforms existing annotations and is useful for downstream tasks. |
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| Challenge: | a crowd-sourced approach to learning semantic parsers to predict predicateargument structures is open to many researchers. |
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| Challenge: | Explicit representations of predicate-argument relations are a cornerstone of natural language understanding. |
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| Challenge: | Question-answering (QA) data often encodes essential information in many facets . a growing interest of QA has led to many large-scale QA datasets available to the community . |
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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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Question Answering Infused Pre-training of General-Purpose Contextualized Representations (2022.findings-acl)
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| Challenge: | Existing pretraining objectives for question answering (QA) are not optimized for being immediately useful without fine-tuning. |
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UNIFIEDQA: Crossing Format Boundaries with a Single QA System (2020.findings-emnlp)
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Daniel Khashabi, Sewon Min, Tushar Khot, Ashish Sabharwal, Oyvind Tafjord, Peter Clark, Hannaneh Hajishirzi
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Bridging Anaphora Resolution as Question Answering (2020.acl-main)
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| Challenge: | Existing studies on bridging anaphora resolution focus on question answering based on context . briding anaphorisms and their antecedents are linked via various lexico-semantic, frame or encyclopedic relations. |
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Crowdsourcing Question-Answer Meaning Representations (N18-2)
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| Challenge: | Existing datasets for predicate-argument relationships are lacking highly skilled and trained annotators. |
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Controlled Crowdsourcing for High-Quality QA-SRL Annotation (2020.acl-main)
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Paul Roit, Ayal Klein, Daniela Stepanov, Jonathan Mamou, Julian Michael, Gabriel Stanovsky, Luke Zettlemoyer, Ido Dagan
| Challenge: | Question-answer driven Semantic Role Labeling (QA-SRL) is an open and natural flavour of SRL, potentially attainable from laymen. |
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