A Dataset for N-ary Relation Extraction of Drug Combinations

Aryeh Tiktinsky; Vijay Viswanathan; Danna Niezni; Dana Meron Azagury; Yosi Shamay; Hillel Taub-Tabib; Tom Hope; Yoav Goldberg

doi:10.18653/v1/2022.naacl-main.233

A Dataset for N-ary Relation Extraction of Drug Combinations

Aryeh Tiktinsky
, Vijay Viswanathan
, Danna Niezni
, Dana Meron Azagury
, Yosi Shamay
, Hillel Taub-Tabib
, Tom Hope
, Yoav Goldberg

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

13 Scopus citations

Abstract

Combination therapies have become the standard of care for diseases such as cancer, tuberculosis, malaria and HIV. However, the combinatorial set of available multi-drug treatments creates a challenge in identifying effective combination therapies available in a situation. To assist medical professionals in identifying beneficial drug-combinations, we construct an expert-annotated dataset for extracting information about the efficacy of drug combinations from the scientific literature. Beyond its practical utility, the dataset also presents a unique NLP challenge, as the first relation extraction dataset consisting of variable-length relations. Furthermore, the relations in this dataset predominantly require language understanding beyond the sentence level, adding to the challenge of this task. We provide a promising baseline model and identify clear areas for further improvement. We release our dataset, code, and baseline models publicly to encourage the NLP community to participate in this task.

Original language	English
Title of host publication	NAACL 2022 - 2022 Conference of the North American Chapter of the Association for Computational Linguistics
Subtitle of host publication	Human Language Technologies, Proceedings of the Conference
Publisher	Association for Computational Linguistics (ACL)
Pages	3190-3203
Number of pages	14
ISBN (Electronic)	9781955917711
DOIs	https://doi.org/10.18653/v1/2022.naacl-main.233
State	Published - 1 Jan 2022
Externally published	Yes
Event	2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL 2022 - Hybrid, Seattle, United States Duration: 10 Jul 2022 → 15 Jul 2022

Publication series

Name	NAACL 2022 - 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference

Conference

Conference	2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL 2022
Country/Territory	United States
City	Hybrid, Seattle
Period	10/07/22 → 15/07/22

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

ASJC Scopus subject areas

Computer Networks and Communications
Hardware and Architecture
Information Systems
Software

Access to Document

10.18653/v1/2022.naacl-main.233

Cite this

Tiktinsky, A., Viswanathan, V., Niezni, D., Azagury, D. M., Shamay, Y., Taub-Tabib, H., Hope, T., & Goldberg, Y. (2022). A Dataset for N-ary Relation Extraction of Drug Combinations. In NAACL 2022 - 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference (pp. 3190-3203). (NAACL 2022 - 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2022.naacl-main.233

Tiktinsky, Aryeh ; Viswanathan, Vijay ; Niezni, Danna et al. / A Dataset for N-ary Relation Extraction of Drug Combinations. NAACL 2022 - 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference. Association for Computational Linguistics (ACL), 2022. pp. 3190-3203 (NAACL 2022 - 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference).

@inproceedings{cf7cdcefdc6841d48ef5c5d4656a6ea5,

title = "A Dataset for N-ary Relation Extraction of Drug Combinations",

abstract = "Combination therapies have become the standard of care for diseases such as cancer, tuberculosis, malaria and HIV. However, the combinatorial set of available multi-drug treatments creates a challenge in identifying effective combination therapies available in a situation. To assist medical professionals in identifying beneficial drug-combinations, we construct an expert-annotated dataset for extracting information about the efficacy of drug combinations from the scientific literature. Beyond its practical utility, the dataset also presents a unique NLP challenge, as the first relation extraction dataset consisting of variable-length relations. Furthermore, the relations in this dataset predominantly require language understanding beyond the sentence level, adding to the challenge of this task. We provide a promising baseline model and identify clear areas for further improvement. We release our dataset, code, and baseline models publicly to encourage the NLP community to participate in this task.",

author = "Aryeh Tiktinsky and Vijay Viswanathan and Danna Niezni and Azagury, \{Dana Meron\} and Yosi Shamay and Hillel Taub-Tabib and Tom Hope and Yoav Goldberg",

note = "Publisher Copyright: {\textcopyright} 2022 Association for Computational Linguistics.; 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL 2022 ; Conference date: 10-07-2022 Through 15-07-2022",

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doi = "10.18653/v1/2022.naacl-main.233",

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series = "NAACL 2022 - 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference",

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Tiktinsky, A, Viswanathan, V, Niezni, D, Azagury, DM, Shamay, Y, Taub-Tabib, H, Hope, T & Goldberg, Y 2022, A Dataset for N-ary Relation Extraction of Drug Combinations. in NAACL 2022 - 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference. NAACL 2022 - 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference, Association for Computational Linguistics (ACL), pp. 3190-3203, 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL 2022, Hybrid, Seattle, United States, 10/07/22. https://doi.org/10.18653/v1/2022.naacl-main.233

A Dataset for N-ary Relation Extraction of Drug Combinations. / Tiktinsky, Aryeh; Viswanathan, Vijay; Niezni, Danna et al.
NAACL 2022 - 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference. Association for Computational Linguistics (ACL), 2022. p. 3190-3203 (NAACL 2022 - 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A Dataset for N-ary Relation Extraction of Drug Combinations

AU - Tiktinsky, Aryeh

AU - Viswanathan, Vijay

AU - Niezni, Danna

AU - Azagury, Dana Meron

AU - Shamay, Yosi

AU - Taub-Tabib, Hillel

AU - Hope, Tom

AU - Goldberg, Yoav

PY - 2022/1/1

Y1 - 2022/1/1

N2 - Combination therapies have become the standard of care for diseases such as cancer, tuberculosis, malaria and HIV. However, the combinatorial set of available multi-drug treatments creates a challenge in identifying effective combination therapies available in a situation. To assist medical professionals in identifying beneficial drug-combinations, we construct an expert-annotated dataset for extracting information about the efficacy of drug combinations from the scientific literature. Beyond its practical utility, the dataset also presents a unique NLP challenge, as the first relation extraction dataset consisting of variable-length relations. Furthermore, the relations in this dataset predominantly require language understanding beyond the sentence level, adding to the challenge of this task. We provide a promising baseline model and identify clear areas for further improvement. We release our dataset, code, and baseline models publicly to encourage the NLP community to participate in this task.

AB - Combination therapies have become the standard of care for diseases such as cancer, tuberculosis, malaria and HIV. However, the combinatorial set of available multi-drug treatments creates a challenge in identifying effective combination therapies available in a situation. To assist medical professionals in identifying beneficial drug-combinations, we construct an expert-annotated dataset for extracting information about the efficacy of drug combinations from the scientific literature. Beyond its practical utility, the dataset also presents a unique NLP challenge, as the first relation extraction dataset consisting of variable-length relations. Furthermore, the relations in this dataset predominantly require language understanding beyond the sentence level, adding to the challenge of this task. We provide a promising baseline model and identify clear areas for further improvement. We release our dataset, code, and baseline models publicly to encourage the NLP community to participate in this task.

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M3 - Conference contribution

AN - SCOPUS:85138339004

T3 - NAACL 2022 - 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference

SP - 3190

EP - 3203

BT - NAACL 2022 - 2022 Conference of the North American Chapter of the Association for Computational Linguistics

PB - Association for Computational Linguistics (ACL)

T2 - 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL 2022

Y2 - 10 July 2022 through 15 July 2022

ER -

Tiktinsky A, Viswanathan V, Niezni D, Azagury DM, Shamay Y, Taub-Tabib H et al. A Dataset for N-ary Relation Extraction of Drug Combinations. In NAACL 2022 - 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference. Association for Computational Linguistics (ACL). 2022. p. 3190-3203. (NAACL 2022 - 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference). doi: 10.18653/v1/2022.naacl-main.233

A Dataset for N-ary Relation Extraction of Drug Combinations

Abstract

Publication series

Conference

UN SDGs

ASJC Scopus subject areas

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