On Implementing Semantic Relatedness #3
Description
I just found your code while trying to understand the paper and was wondering if you could help me.
In section 4.2, it is said that the first step in investigating relatedness between two sentences is to produce sentence representations of HL and HR using a Tree-LSTM model over each sentence's parse tree. Afterwards, another neural network is introduced which uses the angle and distance of the obtained sentence representation pairs.
My question would be how exactly are the HL and HR obtained using the Tree-LSTM model?
Section 5.2 also mentions a produced constituency parse using PCFG, how is this used with the Tree-LSTM?