Finding Emotion Holder from Bengali Blog Texts---An Unsupervised Syntactic Approach
Dipankar Das, Sivaji Bandyopadhyay · Institutional Repositories DataBase (IRDB) · 2010
Abstract. This paper presents two different approaches for identifying emotion holders from Bengali blog sentences. Two types of strategies yield average agreement measures of 0.78 and 0.80 for annotating emotion holders with respect to all emotion classes. The baseline model is developed based on the combinations of various part-of-speech (POS) features extracted from the phrase-based similarities. The syntactic model is based on the argument structure of the sentences with respect to the verbs. If the acquired argument structure of a Bengali blog sentence with respect to its verb matches with any of the frame syntax retrieved for its equivalent English verb of identical sense from VerbNet, the holder role associated with the English VerbnNet frame is mapped to the appropriate slot in Bengali sentence. The syntactic model with an average F-score of 60.03 % outperforms the baseline model with an average F-score of 50.85 % on 500 test sentences.