Completion norms for 3085 English sentence contexts

Jonathan E. Peelle, Ryland L. Miller, Chad S. Rogers, Brent Spehar, Mitchell S. Sommers, Kristin J. Van Engen

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

In everyday language processing, sentence context affects how readers and listeners process upcoming words. In experimental situations, it can be useful to identify words that are predicted to greater or lesser degrees by the preceding context. Here we report completion norms for 3085 English sentences, collected online using a written cloze procedure in which participants were asked to provide their best guess for the word completing a sentence. Sentences varied between eight and ten words in length. At least 100 unique participants contributed to each sentence. All responses were reviewed by human raters to mitigate the influence of mis-spellings and typographical errors. The responses provide a range of predictability values for 13,438 unique target words, 6790 of which appear in more than one sentence context. We also provide entropy values based on the relative predictability of multiple responses. A searchable set of norms is available at http://sentencenorms.net. Finally, we provide the code used to collate and organize the responses to facilitate additional analyses and future research projects.

Original languageEnglish
Pages (from-to)1795-1799
Number of pages5
JournalBehavior Research Methods
Volume52
Issue number4
DOIs
StatePublished - Aug 1 2020

Keywords

  • cloze probability
  • expectation
  • prediction
  • response entropy
  • sentence processing

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