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-theart individual classifier models on the two tasks.
REF proposed a joint probabilistic model for word sense disambiguation (WSD) of prepositions and SRL of prepositional phrases (PPs), and achieved state-of-the-art results over both tasks.
Joint Learning of Preposition Senses and Semantic Roles of Prepositional Phrases
EMNLP
Computer Science