Learning theories for noun-phrase sentiment composition

The work presented here is an approach to Sentiment Analy- sis from a rule-based, compositional perspective. The proposed approach is characterized by three major points: (a) rules are automatically learned from annotated corpora using Inductive Logic Programming and represented as Prolog sets of clauses, (b) the focus is on the noun-phrase (NP) level, and (c) learning is performed on deep-parsed structures. We describe the process of annotating a collection of some 3000 German NPs of medium to quite complex structure, as well as the empirical evaluation of our implementation, in comparison with commonly used classifiers and a handcrafted rule-based system.