Mandarin Relata: A Dataset of Word Relations and Their Semantic Types

Hongchao Liu; Chu Ren Huang; Ren Kui Hou

doi:10.1007/978-3-319-73573-3_30

Mandarin Relata: A Dataset of Word Relations and Their Semantic Types

Hongchao Liu, Chu Ren Huang, Ren Kui Hou

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

Abstract

For both the training and evaluation of semantic distributional models, language datasets are needed that are both elaborate in their word level descriptors and readily intuitive to human judgment. The current paper introduces a dataset for Mandarin Chinese constructed through the combination of word relation pairs from two distinct sources: corpus extraction, and human elicitation. Our results show that while more word relation pairs were gained through the corpus extraction process, human elicited semantic neighbors were almost twice as likely to show agreement with human raters. The current methods created 4091 word relation pairs that span hypernymy, hyponymy, synonymy, antonymy, and meronymy alongside semantic type information. To date, this is the largest collection of human-rated word relation pairs in Mandarin Chinese.

Original language	English
Title of host publication	Chinese Lexical Semantics - 18th Workshop, CLSW 2017, Revised Selected Papers
Editors	Yunfang Wu, Qi Su, Jia-Fei Hong
Publisher	Springer-Verlag
Pages	336-340
Number of pages	5
ISBN (Print)	9783319735726
DOIs	https://doi.org/10.1007/978-3-319-73573-3_30
Publication status	Published - 1 Jan 2018
Event	18th Chinese Lexical Semantics Workshop, CLSW 2017 - Leshan, China Duration: 18 May 2017 → 20 May 2017

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10709 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	18th Chinese Lexical Semantics Workshop, CLSW 2017
Country/Territory	China
City	Leshan
Period	18/05/17 → 20/05/17

Keywords

Dataset
DSM
Semantic types
Word relation

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

More information

10.1007/978-3-319-73573-3_30

Cite this

Liu, H., Huang, C. R., & Hou, R. K. (2018). Mandarin Relata: A Dataset of Word Relations and Their Semantic Types. In Y. Wu, Q. Su, & J-F. Hong (Eds.), Chinese Lexical Semantics - 18th Workshop, CLSW 2017, Revised Selected Papers (pp. 336-340). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10709 LNAI). Springer-Verlag. https://doi.org/10.1007/978-3-319-73573-3_30

Liu, Hongchao ; Huang, Chu Ren ; Hou, Ren Kui. / Mandarin Relata : A Dataset of Word Relations and Their Semantic Types. Chinese Lexical Semantics - 18th Workshop, CLSW 2017, Revised Selected Papers. editor / Yunfang Wu ; Qi Su ; Jia-Fei Hong. Springer-Verlag, 2018. pp. 336-340 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{9c49c517ba4d4b3383a80ff0138758b4,

title = "Mandarin Relata: A Dataset of Word Relations and Their Semantic Types",

abstract = "For both the training and evaluation of semantic distributional models, language datasets are needed that are both elaborate in their word level descriptors and readily intuitive to human judgment. The current paper introduces a dataset for Mandarin Chinese constructed through the combination of word relation pairs from two distinct sources: corpus extraction, and human elicitation. Our results show that while more word relation pairs were gained through the corpus extraction process, human elicited semantic neighbors were almost twice as likely to show agreement with human raters. The current methods created 4091 word relation pairs that span hypernymy, hyponymy, synonymy, antonymy, and meronymy alongside semantic type information. To date, this is the largest collection of human-rated word relation pairs in Mandarin Chinese.",

keywords = "Dataset, DSM, Semantic types, Word relation",

author = "Hongchao Liu and Huang, {Chu Ren} and Hou, {Ren Kui}",

year = "2018",

month = jan,

day = "1",

doi = "10.1007/978-3-319-73573-3_30",

language = "English",

isbn = "9783319735726",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer-Verlag",

pages = "336--340",

editor = "Yunfang Wu and Qi Su and Jia-Fei Hong",

booktitle = "Chinese Lexical Semantics - 18th Workshop, CLSW 2017, Revised Selected Papers",

note = "18th Chinese Lexical Semantics Workshop, CLSW 2017 ; Conference date: 18-05-2017 Through 20-05-2017",

}

Liu, H, Huang, CR & Hou, RK 2018, Mandarin Relata: A Dataset of Word Relations and Their Semantic Types. in Y Wu, Q Su & J-F Hong (eds), Chinese Lexical Semantics - 18th Workshop, CLSW 2017, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10709 LNAI, Springer-Verlag, pp. 336-340, 18th Chinese Lexical Semantics Workshop, CLSW 2017, Leshan, China, 18/05/17. https://doi.org/10.1007/978-3-319-73573-3_30

Mandarin Relata: A Dataset of Word Relations and Their Semantic Types. / Liu, Hongchao; Huang, Chu Ren; Hou, Ren Kui.
Chinese Lexical Semantics - 18th Workshop, CLSW 2017, Revised Selected Papers. ed. / Yunfang Wu; Qi Su; Jia-Fei Hong. Springer-Verlag, 2018. p. 336-340 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10709 LNAI).

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

TY - GEN

T1 - Mandarin Relata

T2 - 18th Chinese Lexical Semantics Workshop, CLSW 2017

AU - Liu, Hongchao

AU - Huang, Chu Ren

AU - Hou, Ren Kui

PY - 2018/1/1

Y1 - 2018/1/1

N2 - For both the training and evaluation of semantic distributional models, language datasets are needed that are both elaborate in their word level descriptors and readily intuitive to human judgment. The current paper introduces a dataset for Mandarin Chinese constructed through the combination of word relation pairs from two distinct sources: corpus extraction, and human elicitation. Our results show that while more word relation pairs were gained through the corpus extraction process, human elicited semantic neighbors were almost twice as likely to show agreement with human raters. The current methods created 4091 word relation pairs that span hypernymy, hyponymy, synonymy, antonymy, and meronymy alongside semantic type information. To date, this is the largest collection of human-rated word relation pairs in Mandarin Chinese.

AB - For both the training and evaluation of semantic distributional models, language datasets are needed that are both elaborate in their word level descriptors and readily intuitive to human judgment. The current paper introduces a dataset for Mandarin Chinese constructed through the combination of word relation pairs from two distinct sources: corpus extraction, and human elicitation. Our results show that while more word relation pairs were gained through the corpus extraction process, human elicited semantic neighbors were almost twice as likely to show agreement with human raters. The current methods created 4091 word relation pairs that span hypernymy, hyponymy, synonymy, antonymy, and meronymy alongside semantic type information. To date, this is the largest collection of human-rated word relation pairs in Mandarin Chinese.

KW - Dataset

KW - DSM

KW - Semantic types

KW - Word relation

UR - http://www.scopus.com/inward/record.url?scp=85045322266&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-73573-3_30

DO - 10.1007/978-3-319-73573-3_30

M3 - Conference article published in proceeding or book

AN - SCOPUS:85045322266

SN - 9783319735726

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 336

EP - 340

BT - Chinese Lexical Semantics - 18th Workshop, CLSW 2017, Revised Selected Papers

A2 - Wu, Yunfang

A2 - Su, Qi

A2 - Hong, Jia-Fei

PB - Springer-Verlag

Y2 - 18 May 2017 through 20 May 2017

ER -

Liu H, Huang CR, Hou RK. Mandarin Relata: A Dataset of Word Relations and Their Semantic Types. In Wu Y, Su Q, Hong J-F, editors, Chinese Lexical Semantics - 18th Workshop, CLSW 2017, Revised Selected Papers. Springer-Verlag. 2018. p. 336-340. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-73573-3_30

Mandarin Relata: A Dataset of Word Relations and Their Semantic Types

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

More information

Other files and links

Fingerprint

Cite this