Abstract
This paper provides a computable quantitative measure which accounts for the difficulty in human processing of sentences: why is a sentence harder to parse than another one? Why is some reading of a sentence easier than another one? We take for granted psycholinguistic results on human processing complexity like the ones by Gibson. We define a new metric which uses Categorial Proof Nets to correctly model Gibson’s account in his Dependency Locality Theory. The proposed metric correctly predicts some performance phenomena such as structures with embedded pronouns, garden paths, unacceptable center embeddings, preference for lower attachment and passive paraphrases acceptability. Our proposal gets closer to the modern computational psycholinguistic theories, while it opens the door to include semantic complexity, because of the straightforward syntax-semantics interface in categorial grammars.
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Notes
- 1.
- 2.
Here we are stricter than in other articles, i.e. we neither allow \(\otimes \) of positive formulas nor
of negative formulas, because we only use the \(\mathbin {\backslash }\) and \(\mathbin {/}\) symbols in categories (and not \(\otimes \)): only combining heterogeneous polarities guarantees that a positive formula is a category, and that a negative formula is the negation of a category. - 3.
This list is redundant: for instance intuitionism plus acyclicity implies connectedness.
- 4.
The same procedure can show the increasing complexity of the examples (1a)–(1c) by drawing the relevant proof-nets. This practice is avoided in this paper due the space limitation and its simplicity comparing to the running examples.
- 5.
Following Lambek [12], we have assigned the category \(S / (np \backslash S)\) to relative pronoun I. Note that even assigning np, which is not a type-shifted category, would not change our numeric analysis at all.
- 6.
It is worth mentioning that DLT-based complexity profiling can not support two linguistic phenomena: Multiple Sentences and Heavy Noun-Phrase Shift. For more details on the problem related to the Multiple-Quantifier Sentences and a possible solution consider [20, Chaps. 5 and 7].
of negative formulas, because we only use the References
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Mirzapour, M., Prost, JP., Retoré, C. (2020). Measuring Linguistic Complexity: Introducing a New Categorial Metric. In: Loukanova, R. (eds) Logic and Algorithms in Computational Linguistics 2018 (LACompLing2018). Studies in Computational Intelligence, vol 860. Springer, Cham. https://doi.org/10.1007/978-3-030-30077-7_5
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