The paper “Syntactic and Semantic Structure for Opinion Expression Detection” co-written by R. Johansson and A. Moschitti has been presented at CoNLL 2010 in Uppsala, Sweden on July 15th-16th, 2010
In this paper we demonstrate that relational features derived from dependency-syntactic and semantic role structures are useful for the task of detecting opinionated expressions in natural-language text, significantly improving over conventional models based on sequence labeling with local features. These features allow us to model the way opinionated expressions interact in a sentence over arbitrary distances.
While the relational features make the prediction task more computationally expensive, we show that it can be tackled effectively by using a reranker. We evaluate a number of machine learning approaches for the reranker, and the best model results in a 10-point absolute improvement in soft recall on the MPQA corpus, while decreasing precision only slightly.
The LK project is funded by the European Commission under Project No. 231126