Bilateral Multi-Perspective Matching for Natural Language Sentences
Table 4: Performance for answer sentence selection on TREC-QA and WikiQA datasets.
['Models', 'TREC-QA MAP', 'TREC-QA MRR', 'WikiQA MAP', 'WikiQA MRR']
In this Sub-section, we study the effectiveness of our model for answer sentence selection tasks. The answer sentence selection task is to rank a list of candidate answer sentences based on their similarities to the question, and the performance is measured by the mean average precision (MAP) and mean reciprocal rank (MRR). We can see that the performance from our model is on par with the state-of-the-art models. Therefore, our model is also effective for answer sentence selection tasks.