Papers by Michael Bugert

3 papers
Revisiting Joint Modeling of Cross-document Entity and Event Coreference Resolution (P19-1)

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Challenge: Recognizing that various textual spans across multiple texts refer to the same entity or event is an important NLP task.
Approach: They propose a neural architecture for cross-document coreference resolution by representing an event mention using its lexical span, surrounding context, and relation to other mentions via predicate-arguments structures.
Outcome: The proposed model outperforms the state-of-the-art event coreference model on ECB+ while providing the first entity coreference results on this corpus.
The INCEpTION Platform: Machine-Assisted and Knowledge-Oriented Interactive Annotation (C18-2)

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Challenge: INCEpTION is an annotation platform for interactive and semantic annotation . the platform is both generic and modular .
Approach: INCEpTION is an annotation platform for interactive and semantic annotation . the platform incorporates machine learning capabilities which actively assist annotators .
Outcome: INCEpTION is an open-source annotation platform for tasks including interactive and semantic annotation.
Event Coreference Data (Almost) for Free: Mining Hyperlinks from Online News (2021.emnlp-main)

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Challenge: Annotating CDCR data is laborious and expensive, explaining why existing corpora are small and lack domain coverage.
Approach: They use hyperlinks to extract event coreference data from online news articles . they find that models trained on small subsets of HyperCoref are highly competitive .
Outcome: The proposed system frees up CDCR research from costly human-annotated training data and opens up possibilities beyond English.

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