I am trying to find if a given word/ set of words are similar to a definition. Example - Definition - "vegetarian User" Now, if I want to check a set of sentences like below sentences = ['vegetarian User', 'user sometimes eats chicken', 'user is vegetarian', 'user only eats fruits', 'user likes fish'] I tried using some sentence transformer like below model = SentenceTransformer("all-mpnet-base-v2") embeddings = model.encode(sentences) similarities = model.similarity(embeddings,embeddings) print(similarities) But this is not giving me expected results. What is the best approach to achieve results like below? [False,True,True,False] Is it doable with nlp/ some other technique? Continue reading...
