Abstract
This work investigates the application of a measure of surprisal to modeling a grammatical variation phenomenon between near-synonymous constructions. We investigate a particular variation phenomenon, word order variation in Dutch two-verb clusters, where it has been established that word order choice is affected by processing cost. Several multifactorial corpus studies of Dutch verb clusters have used other measures of processing complexity to show that this factor affects word order choice. This previous work allows us to compare the surprisal measure, which is based on constraint satisfaction theories of language modeling, to those previously used measures, which are more directly linked to empirical observations of processing complexity. Our results show that surprisal does not predict the word order choice by itself, but is a significant predictor when used in a measure of uniform information density (UID). This lends support to the view that human language processing is facilitated not so much by predictable sequences of words but more by sequences of words in which information is spread evenly.- Anthology ID:
- W16-4120
- Volume:
- Proceedings of the Workshop on Computational Linguistics for Linguistic Complexity (CL4LC)
- Month:
- December
- Year:
- 2016
- Address:
- Osaka, Japan
- Venue:
- CL4LC
- SIG:
- Publisher:
- The COLING 2016 Organizing Committee
- Note:
- Pages:
- 174–185
- Language:
- URL:
- https://aclanthology.org/W16-4120
- DOI:
- Cite (ACL):
- Jelke Bloem. 2016. Testing the Processing Hypothesis of word order variation using a probabilistic language model. In Proceedings of the Workshop on Computational Linguistics for Linguistic Complexity (CL4LC), pages 174–185, Osaka, Japan. The COLING 2016 Organizing Committee.
- Cite (Informal):
- Testing the Processing Hypothesis of word order variation using a probabilistic language model (Bloem, CL4LC 2016)
- PDF:
- https://preview.aclanthology.org/remove-xml-comments/W16-4120.pdf