Search Results for author: Valentina Pyatkin

Found 11 papers, 6 papers with code

QADiscourse - Discourse Relations as QA Pairs: Representation, Crowdsourcing and Baselines

no code implementations EMNLP 2020 Valentina Pyatkin, Ayal Klein, Reut Tsarfaty, Ido Dagan

Discourse relations describe how two propositions relate to one another, and identifying them automatically is an integral part of natural language understanding.

Natural Language Understanding

Design Choices in Crowdsourcing Discourse Relation Annotations: The Effect of Worker Selection and Training

no code implementations LREC 2022 Merel Scholman, Valentina Pyatkin, Frances Yung, Ido Dagan, Reut Tsarfaty, Vera Demberg

The current contribution studies the effect of worker selection and training on the agreement on implicit relation labels between workers and gold labels, for both the DC and the QA method.

Just-DREAM-about-it: Figurative Language Understanding with DREAM-FLUTE

1 code implementation28 Oct 2022 Yuling Gu, Yao Fu, Valentina Pyatkin, Ian Magnusson, Bhavana Dalvi Mishra, Peter Clark

We hypothesize that to perform this task well, the reader needs to mentally elaborate the scene being described to identify a sensible meaning of the language.

Pretrained Language Models

QASem Parsing: Text-to-text Modeling of QA-based Semantics

1 code implementation23 May 2022 Ayal Klein, Eran Hirsch, Ron Eliav, Valentina Pyatkin, Avi Caciularu, Ido Dagan

Several recent works have suggested to represent semantic relations with questions and answers, decomposing textual information into separate interrogative natural language statements.

Data Augmentation

Asking It All: Generating Contextualized Questions for any Semantic Role

1 code implementation EMNLP 2021 Valentina Pyatkin, Paul Roit, Julian Michael, Reut Tsarfaty, Yoav Goldberg, Ido Dagan

We develop a two-stage model for this task, which first produces a context-independent question prototype for each role and then revises it to be contextually appropriate for the passage.

Question Generation Question-Generation

The Possible, the Plausible, and the Desirable: Event-Based Modality Detection for Language Processing

2 code implementations ACL 2021 Valentina Pyatkin, Shoval Sadde, Aynat Rubinstein, Paul Portner, Reut Tsarfaty

Modality is the linguistic ability to describe events with added information such as how desirable, plausible, or feasible they are.

QANom: Question-Answer driven SRL for Nominalizations

1 code implementation COLING 2020 Ayal Klein, Jonathan Mamou, Valentina Pyatkin, Daniela Stepanov, Hangfeng He, Dan Roth, Luke Zettlemoyer, Ido Dagan

We propose a new semantic scheme for capturing predicate-argument relations for nominalizations, termed QANom.

QADiscourse -- Discourse Relations as QA Pairs: Representation, Crowdsourcing and Baselines

1 code implementation6 Oct 2020 Valentina Pyatkin, Ayal Klein, Reut Tsarfaty, Ido Dagan

Discourse relations describe how two propositions relate to one another, and identifying them automatically is an integral part of natural language understanding.

Natural Language Understanding

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