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Systems and methods for natural language processing (NLP) are described. The systems may be trained by identifying training data including clean data and noisy data; predicting annotation information using an artificial neural network (ANN); computing a loss value for the annotation information using a weighted loss function that applies a first weight to the clean data and at least one second weight to the noisy data; and updating the ANN based on the loss value.

In some embodiments, a knowledge graph generation system extracts noun-phrases from sentences of a knowledge corpora and determines the relations between the noun-phrases based on a relation classifier that is configured to predict a relation between a pair of entities without restricting the entities to a set of named entities. The knowledge graph generation system further generates a sub-graph for each of the sentences based on the noun-phrases and the determined relations.