Abstract
The sense of a preposition is related to the semantics of its dominating prepositional phrase. Knowing the sense of a preposition could help to correctly classify the semantic role of the dominating prepositional phrase and vice versa. In this paper, we propose a joint probabilistic model for word sense disambiguation of prepositions and semantic role labeling of prepositional phrases. Our experiments on the PropBank corpus show that jointly learning the word sense and the semantic role leads to an improvement over state-of-the-art individual classifier models on the two tasks.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
