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Recognizing semantic relation in sentence pairs using Tree-RNNs and Typed dependencies
Recursive neural networks (Tree-RNNs) based on dependency trees are ubiquitous in modeling sentence meanings as they effectively capture semantic relationships between non-neighborhood words.
An enhanced Tree-LSTM architecture for sentence semantic modeling using typed dependencies
However, most of these models cannot recognize the difference in meaning caused by a change in semantic roles of words or phrases because they do not acknowledge the type of grammatical relations, also known as typed dependencies, in sentence structure.
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