Multi−entity Sentiment Scoring
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 ceilin...
Main Authors: | , |
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Format: | Conference item |
Published: |
2015
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Summary: | 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. |
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