Abstract
It is well-known that readers are less likely to fixate their gaze on closed class syntactic categories such as prepositions and pronouns. This paper investigates to what extent the syntactic category of a word in context can be predicted from gaze features obtained using eye-tracking equipment. If syntax can be reliably predicted from eye movements of readers, it can speed up linguistic annotation substantially, since reading is considerably faster than doing linguistic annotation by hand. Our results show that gaze features do discriminate between most pairs of syntactic categories, and we show how we can use this to annotate words with part of speech across domains, when tag dictionaries enable us to narrow down the set of potential categories.
| Original language | English |
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| Title of host publication | The 19th Conference on Computational Natural Language Learning : CoNLL |
| Number of pages | 5 |
| Publisher | Association for Computational Linguistics |
| Publication date | 2015 |
| Pages | 345-349 |
| ISBN (Print) | 978-1-941643-77-8 |
| Publication status | Published - 2015 |