Evidence map›Paper›PMID 41184263›Full record

ArticleScientific data2025

An open dataset of Chinese duration expressions.

Si-Qi Zhang, Jia-Wen Niu, Xiaoqian Liu, Xiao-Yang Sui, Li-Lin Rao

Abstract readDataset
In one paragraph

Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

5 authors.

Si-Qi Zhang *State Key Laboratory of Cognitive Science and Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.ORCID 0000-0002-1730-6589
Jia-Wen Niu *State Key Laboratory of Cognitive Science and Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.
Xiaoqian LiuState Key Laboratory of Cognitive Science and Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.
Xiao-Yang SuiSchool of Sociology and Psychology, Central University of Finance and Economics, Beijing, China. suixy@cufe.edu.cn.
Li-Lin RaoState Key Laboratory of Cognitive Science and Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China. raoll@psych.ac.cn.ORCID 0000-0002-4542-9981

Funding

National Natural Science Foundation of China (National Science Foundation of China) 72371237National Natural Science Foundation of China (National Science Foundation of China) 92046006
6 · The paper itself

Abstract

Duration information is essential for understanding and analyzing our world. In textual contexts, duration information is typically conveyed in two formats: numeric (e.g., 1 hour) and verbal (e.g., shortly). To analyze duration information in text, it is crucial to understand how people map duration expressions to corresponding numerical duration. However, the literature has yet to provide lexicons supporting such conversion. Furthermore, existing databases of time-related expressions often lack information about word frequency - a robust predictor of information processing. This article reports an open dataset of 2,101 Chinese duration expressions, each annotated with its corresponding numerical duration. To obtain high-quality data for word frequency, we obtained the frequency of each duration expression from a large-scale corpus of 10 billion Chinese characters (BLCU Corpus Center (BCC) Corpus) and computed an adjusted frequency for each expression. This dataset provides a valuable resource for research on temporal information in Chinese, facilitating studies in natural language processing, psychology, and linguistics.

Indexed as

LanguageChinaHumansLinguisticsNatural Language Processing

Identifiers

PMID41184263
PMCPMC12583718

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.