Grammatical cues to subjecthood are redundant in a majority of simple clauses across languages
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Abstract (arXiv)
Grammatical cues are sometimes redundant with word meanings in natural language. For instance, English word order rules constrain the word order of a sentence like "The dog chewed the bone" even though the status of "dog" as subject and "bone" as object can be inferred from world knowledge and plausibility. Quantifying how often this redundancy occurs, and how the level of redundancy varies across typologically diverse languages, can shed light on the function and evolution of grammar. To that end, we performed a behavioral experiment in English and Russian and a cross-linguistic computational analysis measuring the redundancy of grammatical cues in transitive clauses extracted from corpus text. English and Russian speakers (n=484) were presented with subjects, verbs, and objects (in random order and with morphological markings removed) extracted from naturally occurring sentences and were asked to identify which noun is the subject of the action. Accuracy was high in both languages (~89% in English, ~87% in Russian). Next, we trained a neural network machine classifier on a similar task: predicting which nominal in a subject-verb-object triad is the subject. Across 30 languages from eight language families, performance was consistently high: a median accuracy of 87%, comparable to the accuracy observed in the human experiments. The conclusion is that grammatical cues such as word order are necessary to convey subjecthood and objecthood in a minority of naturally occurring transitive clauses; nevertheless, they can (a) provide an important source of redundancy and (b) are crucial for conveying intended meaning that cannot be inferred from the words alone, including descriptions of human interactions, where roles are often reversible (e.g., Ray helped Lu/Lu helped Ray), and expressing non-prototypical meanings (e.g., "The bone chewed the dog.").
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 17 of its 119 references that are in the map. First posted on arXiv 30 Jan 2022.
Builds on
17 of 119 references.
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5 more
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Citing papers per year: 2022: 1; 2023: 2; 2024: 0; 2025: 1; 2026: 1.
5 papers.
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- 2023A Cross-Linguistic Pressure for Uniform Information Density in Word Order6 Jun 2023
- 2023Language Model Behavior: A Comprehensive Survey20 Mar 2023
- 2022Event knowledge in large language models: the gap between the impossible and the unlikely2 Dec 2022