Fine-Grained Entity Typing for Domain Independent Entity Linking
national conference on artificial intelligence, 2020.
Neural entity linking models are very powerful, but run the risk of overfitting to the domain they are trained in. For this problem, a domain can be narrowly construed as a particular distribution of entities, as models can even overfit by memorizing properties of specific frequent entities in a dataset. We tackle the problem of buildin...More
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