@inproceedings{dryjanski-etal-2022-samsung,
title = "{S}amsung Research {P}oland ({SRPOL}) at {S}em{E}val-2022 Task 9: Hybrid Question Answering Using Semantic Roles",
author = "Dryja{\'n}ski, Tomasz and
Zaleska, Monika and
Ku{\'z}ma, Bartek and
B{\l}a{\.z}ejewski, Artur and
Bordzicka, Zuzanna and
Bujnowski, Pawe{\l} and
Firlag, Klaudia and
Goltz, Christian and
Grabowski, Maciej and
Jo{\'n}czyk, Jakub and
K{\l}osi{\'n}ski, Grzegorz and
Paziewski, Bart{\l}omiej and
Paszkiewicz, Natalia and
Piersa, Jaros{\l}aw and
Andruszkiewicz, Piotr",
editor = "Emerson, Guy and
Schluter, Natalie and
Stanovsky, Gabriel and
Kumar, Ritesh and
Palmer, Alexis and
Schneider, Nathan and
Singh, Siddharth and
Ratan, Shyam",
booktitle = "Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)",
month = jul,
year = "2022",
address = "Seattle, United States",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.semeval-1.178",
doi = "10.18653/v1/2022.semeval-1.178",
pages = "1263--1273",
abstract = "In this work we present an overview of our winning system for the R2VQ - Competence-based Multimodal Question Answering task, with the final exact match score of 92.53{\%}.The task is structured as question-answer pairs, querying how well a system is capable of competence-based comprehension of recipes. We propose a hybrid of a rule-based system, Question Answering Transformer, and a neural classifier for N/A answers recognition. The rule-based system focuses on intent identification, data extraction and response generation.",
}
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<abstract>In this work we present an overview of our winning system for the R2VQ - Competence-based Multimodal Question Answering task, with the final exact match score of 92.53%.The task is structured as question-answer pairs, querying how well a system is capable of competence-based comprehension of recipes. We propose a hybrid of a rule-based system, Question Answering Transformer, and a neural classifier for N/A answers recognition. The rule-based system focuses on intent identification, data extraction and response generation.</abstract>
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%0 Conference Proceedings
%T Samsung Research Poland (SRPOL) at SemEval-2022 Task 9: Hybrid Question Answering Using Semantic Roles
%A Dryjański, Tomasz
%A Zaleska, Monika
%A Kuźma, Bartek
%A Błażejewski, Artur
%A Bordzicka, Zuzanna
%A Bujnowski, Paweł
%A Firlag, Klaudia
%A Goltz, Christian
%A Grabowski, Maciej
%A Jończyk, Jakub
%A Kłosiński, Grzegorz
%A Paziewski, Bartłomiej
%A Paszkiewicz, Natalia
%A Piersa, Jarosław
%A Andruszkiewicz, Piotr
%Y Emerson, Guy
%Y Schluter, Natalie
%Y Stanovsky, Gabriel
%Y Kumar, Ritesh
%Y Palmer, Alexis
%Y Schneider, Nathan
%Y Singh, Siddharth
%Y Ratan, Shyam
%S Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)
%D 2022
%8 July
%I Association for Computational Linguistics
%C Seattle, United States
%F dryjanski-etal-2022-samsung
%X In this work we present an overview of our winning system for the R2VQ - Competence-based Multimodal Question Answering task, with the final exact match score of 92.53%.The task is structured as question-answer pairs, querying how well a system is capable of competence-based comprehension of recipes. We propose a hybrid of a rule-based system, Question Answering Transformer, and a neural classifier for N/A answers recognition. The rule-based system focuses on intent identification, data extraction and response generation.
%R 10.18653/v1/2022.semeval-1.178
%U https://aclanthology.org/2022.semeval-1.178
%U https://doi.org/10.18653/v1/2022.semeval-1.178
%P 1263-1273
Markdown (Informal)
[Samsung Research Poland (SRPOL) at SemEval-2022 Task 9: Hybrid Question Answering Using Semantic Roles](https://aclanthology.org/2022.semeval-1.178) (Dryjański et al., SemEval 2022)
ACL
- Tomasz Dryjański, Monika Zaleska, Bartek Kuźma, Artur Błażejewski, Zuzanna Bordzicka, Paweł Bujnowski, Klaudia Firlag, Christian Goltz, Maciej Grabowski, Jakub Jończyk, Grzegorz Kłosiński, Bartłomiej Paziewski, Natalia Paszkiewicz, Jarosław Piersa, and Piotr Andruszkiewicz. 2022. Samsung Research Poland (SRPOL) at SemEval-2022 Task 9: Hybrid Question Answering Using Semantic Roles. In Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022), pages 1263–1273, Seattle, United States. Association for Computational Linguistics.