Semantic Parsing to Probabilistic Programs for Situated Question Answering
Table 4: Accuracy on the scene data set. KK2013 results are from Krishnamurthy and Kollar (2013).
['Model', 'Supervision QA', 'Supervision QA+E', 'Supervision QA+E+LF']
The evaluation metric is exact match accuracy between the predicted and labeled sets of objects. We consider three supervision conditions: QA trains with question/answer pairs, QA+E further includes labeled environments, and QA+E+LF further includes labeled logical forms. We trained P3 in the first two conditions, while prior work trained in the first and third conditions. KK2013 is a possible worlds model with a max-margin training objective. P3 slightly outperforms in the QA condition and P3 trained with labeled environments outperforms prior work trained with additional logical form labels.