uwittygit

关于论文里在 complexWebQuesion 数据集上与pullNet的对比

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在论文里有写到 SPARQA在 complexWebQuesion数据集上准确率为 31.57% 低于PullNet（45.9%），是因为PullNet使用了额外的文档数据集。但是我回去找PullNet论文的数据，它说：“ On the test set, our model has 45.9% Hits@1 in the KB only setting ” 。这是怎么回事呢？ 论文的这种PipeLine的方式，我觉得在工程应用上有前途，可控！但是文中各个模块是单独训练的，没有像PullNet那样把各个模块串起来做若监督训练，是不是有提升空间？ 有空交流下，多谢。

possible improvement of accuracy in sempre1.0

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Hi, Liang I think there is a bug in sempre1.0. you may try to fix it and see a significant accuracy improvement. Location: src/edu/stanford/nlp/sempre/paraphrase/VectorSpaceModel.java in function computeSimilarity, line 133. where...

Problems when update params

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Hi, Liang I used Sempre1.0 paraphrase for test, and I only used the alignment and VSM features, no paraphrase features was adoped, such as "Denotation Features", "Formula Features", "Wh- type...