Enhancing Opinion Role Labeling with Semantic-Aware Word Representations from Semantic Role Labeling
Holder Binary F1: 84.91Target Binary F1: 73.29
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Fine-Grained Opinion Analysis
Fine-Grained Opinion Analysis aims to: (i) detect opinion expressions that convey attitudes such as sentiments, agreements, beliefs, or intentions, (ii) measure their intensity, (iii) identify their holders i.e. entities that express an attitude, (iv) identify their targets i.e. entities or propositions at which the attitude is directed, and (v) classify their target-dependent attitude.
<span style="color:grey; opacity: 0.6">( Image credit: SRL4ORL )</span>
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F1 (Opinion): 65.28F1 (Opinion-Role Pair): 51.62F1 (Opinion-Holder Pair): 59.48F1 (Opinion-Target Pair): 44.04
Holder Binary F1: 83.80Target Binary F1: 72.06
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