A controlled reading time dataset for modeling human sentence processing difficulty
收藏DataCite Commons2026-04-24 更新2026-05-04 收录
下载链接：
https://nakala.fr/10.34847/nkl.7c467lyv
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资源简介：
We present a large-scale, controlled self-paced reading dataset designed to isolate the effects of dependency length on human reading times. It bridges the gap between large but naturalistic NLP corpora and small but controlled psycholinguistic datasets.
If you use this dataset, please cite:
Nusbaumer, N., de-Dios-Flores, I., Bel, C., Pallier, C., Wisniewski, G., Crabbé, B. (2025). A large-scale controlled self-paced reading dataset for evaluating dependency length effects across syntactic structures. (Paper forthcoming — citation will be updated upon publication.)
提供机构：
NAKALA - https://nakala.fr (Huma-Num - CNRS)
创建时间：
2026-03-25
