Papers with multi-instance learning problem

1 papers
Distant Learning for Entity Linking with Automatic Noise Detection (P19-1)

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Challenge: Accurate entity linkers have been produced for domains and languages where no or very limited amounts of labeled data are available.
Approach: They propose to use annotated text to learn to link entities without labeling . they frame the task as a multi-instance learning problem and rely on surface matching to create initial noisy labels.
Outcome: The proposed method outperforms the baseline surface matching model for a subset of entities.

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