I'm working on an nlp school project in which I have to build a model that takes a text and a claim and gives as an output whether the text is supporting or opposing the claim . . the data that I have is quite small and it contains paragraphs classified as supporting or opposing for only 10 claims. My problem is that I'm used to working on text processing and classification but introducing another variable in the classification like the claim seems confusing for me i don't know am i supposed to handle this issue , should i work only on the 10 claims that i have knowing that the data is really small or is it possible to build a model that is more general



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