Multi−entity Sentiment Scoring
Karo Moilanen and Stephen Pulman
Abstract
We present a compositional framework for modelling entity-level sentiment (sub)contexts, and demonstrate how holistic multi-entity polarity scoring emerges as a by-product of compositional sentiment parsing. A data set of five annotators' multi-entity judgements is presented, and a human ceiling is established for the challenging new task. The accuracy of an initial implementation, which includes both supervised learning and heuristic distance-based scoring methods, is 5.6 6.8 points below the human ceiling amongst sentences and 8.1 8.7 points amongst phrases.
Details
| Book Title |
Proceedings of Recent Advances in Natural Language Processing (RANLP 2009) |
| Location |
Borovets‚ Bulgaria |
| Month |
September 14−16 |
| Pages |
258–263 |
| Year |
2009 |
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