In this episode, we chat with Luke Zettlemoyer about Question Answering as a format for crowdsourcing annotations of various semantic phenomena in text. We start by talking about QA-SRL and QAMR, two datasets that use QA pairs to annotate predicate-argument relations at the sentence level. Luke describes how this annotation scheme makes it possible to obtain annotations from non-experts, and discusses the tradeoffs involved in choosing this scheme. Then we talk about the challenges involved in using QA-based annotations for more complex phenomena like coreference. Finally, we briefly discuss the value of crowd-labeled datasets given the recent developments in pretraining large language models. Luke is an associate professor at the University of Washington and a Research Scientist at Facebook AI Research.

96 - Question Answering as an Annotation Format, with Luke Zettlemoyer

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Welcome to the NLP highlights podcast, where we invite researchers to talk about their work in various areas in natural language processing. All views expressed belong to the hosts/guests, and do not represent their employers.

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96 - Question Answering as an Annotation Format, with Luke Zettlemoyer

NLP Highlights