How to approach for predicting semantic similarity between two phrases I need pointers on the latest research, tools, and techniques for predicting semantic similarity between two phrases.
Problem Statement: Given two propositions A and B with A know to be true, predict if B agrees, contradicts, or is neutral.
Examples
A = X is greater than Y | B = Y is greater than X | Result = contradict
A = X is greater than Y | B = Y is less than X | Result = agree
A = X is greater than Y | B = P is less than X | Result = neutral
A = X increases with Y | B = X is directly proportional to Y | Result = agree
A = X is joining Y and Z | B = Y and Z are connected with X | Result = agree
What I have tried
I am looking into Google's Universal Sentence Encoder and alternatives for evaluating semantic similarities with mixed results. Most of the solutions available will give a result of exactly similar
for the first example. I am also going through some research papers on grammar-based similarity techniques in natural language.
Any help or direction towards research papers, tools, or libraries is greatly appreciated.
What you are describing is one of the &quot;standard&quot; NLP problems faced in NLP and it usually referred to as &quot;natural language inference&quot; (NLI), or sometimes also as &quot;textual entailment&quot;.
There is plenty of research in this kind of task, and its variants, like cross-lingual NLI (XNLI). I suggest you have a look at nlpprogress (link) or paperswithcode (link) to understand the landscape of benchmark datasets and SoTA models in NLI.