Building computers able to answer questions on any subject is a long standing goal of artificial intelligence. Promising progress has recently been achieved by methods that learn to map questions to logical forms or database queries. Such approaches can be effective but at the cost of either large amounts of human-labeled data or by defining lexicons and grammars tailored by practitioners.
|Task||Dataset||Model||Metric name||Metric value||Global rank||Compare|
|Question Answering||Reverb||Weakly Supervised Embeddings||Accuracy||73%||# 1|
|Question Answering||WebQuestions||Weakly Supervised Embeddings||F1||29.7%||# 3|