On the impact of syntactic and semantic information when processing words in sentences

We report the results of two experiments that used the Rapid Parallel Visual Presentation (RPVP) procedure to evaluate the contributions of syntactic and semantic information when identifying words within a sentence context. Participants were presented with five-word sequences that could either be grammatically correct (e.g., <i>"the cat ate fresh food"</i>) or an ungrammatical re-ordering of the same words (e.g., <i>"ate cat food the fresh"</i>). Word sequences were displayed for 200 ms, after which participants were asked to classify a word at a post-cued location - either Position 2, 3, or 4, in the 5-word sequence. In Experiment 1, the classification was based on a syntactic category (is this word a noun or an adjective?). In Experiment 2, the classification was based on retrieval of the object associated with the word (is the object referred to by this word bigger or smaller than 1 m?). Analyses tested for effects of grammaticality on word classification accuracy (i.e., a sentence superiority effect - SSE) per target word position in both experiments. For syntactic classifications (Experiment 1), the SSE was significant at all positions. On the other hand, for semantic classifications, the SSE was only significant at Position 4. We conclude that in the RPVP paradigm readers use both syntactic and semantic information to rapidly build a primitive sentence structure, but with semantic constraints having a later influence. This structure then helps them to associate more detailed syntactic and semantic information to word identities at specific locations within the sentence.

Authors

Institutions

Publication Details

Journal
Quarterly Journal of Experimental Psychology
Published
2025-06-25
DOI
https://doi.org/10.1177/17470218251350584
Primary Topic
Natural Language Processing Techniques
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

On the impact of syntactic and semantic information when processing words in sentences

Jonathan Grainger, Aaron Vandendaele
Quarterly Journal of Experimental Psychology
Natural Language Processing Techniques
article

On the impact of syntactic and semantic information when processing words in sentences

Jonathan Grainger, Aaron Vandendaele
article en

Abstract

We report the results of two experiments that used the Rapid Parallel Visual Presentation (RPVP) procedure to evaluate the contributions of syntactic and semantic information when identifying words within a sentence context. Participants were presented with five-word sequences that could either be grammatically correct (e.g., <i>"the cat ate fresh food"</i>) or an ungrammatical re-ordering of the same words (e.g., <i>"ate cat food the fresh"</i>). Word sequences were displayed for 200 ms, after which participants were asked to classify a word at a post-cued location - either Position 2, 3, or 4, in the 5-word sequence. In Experiment 1, the classification was based on a syntactic category (is this word a noun or an adjective?). In Experiment 2, the classification was based on retrieval of the object associated with the word (is the object referred to by this word bigger or smaller than 1 m?). Analyses tested for effects of grammaticality on word classification accuracy (i.e., a sentence superiority effect - SSE) per target word position in both experiments. For syntactic classifications (Experiment 1), the SSE was significant at all positions. On the other hand, for semantic classifications, the SSE was only significant at Position 4. We conclude that in the RPVP paradigm readers use both syntactic and semantic information to rapidly build a primitive sentence structure, but with semantic constraints having a later influence. This structure then helps them to associate more detailed syntactic and semantic information to word identities at specific locations within the sentence.

Quarterly Journal of Experimental PsychologyVol. 79(3)
Centre National de la Recherche Scientifique (FR), Vrije Universiteit Brussel (BE), Aix-Marseille Université (FR), Ghent University (BE)
Fonds Wetenschappelijk Onderzoek, Vrije Universiteit Brussel, European Research Council
Zero hunger
Openalex Percentile: Top 94%
Natural Language Processing Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.