The present approach aims to identify the emotional expression, holder, topic, and their co-reference from Bengali blog sentences. Two techniques are employed, one is a rule-based baseline system and the other is a supervised system that consists of different syntactic, semantic, rhetorical, and overlapping features. Different error cases have been resolved using rule-based post processing techniques. The evaluative vectors containing emotional expressions, holders, and topics are prepared from annotated blog posts as well as from system generated output. The evaluation metric, Krippendorff’s α, achieves agreement scores of 0.53 and 0.67 for the baseline and supervised co-reference classification systems, respectively.