In an example, for each of one or more terms in a text document, one or more entities to which the term potentially maps are identified. The text document includes at least one ambiguous term. One or more features are extracted from the text document. An attention model is applied to the text document based on the extracted one or more features, resulting in an attention weight being applied to each of the one or more terms in the text document. The one or more terms are encoded based on the attention weights. Each of one or more ambiguous terms is classified based on the encoded terms, the classification assigning a value to each different entity that each ambiguous term potentially maps to. A minimum entropy loss function is evaluated using the classification, and results are back-propagated to the attention model.