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Supervised WithinDocument Event Coreference using Information Propagation Zhengzhou Liu, Jun Arab, Eduard Holy, Peruke McNamara Carnegie Mellon University 5000 Forbes Avenue, Pittsburgh, PA Liu×cs.CMU.edu,
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How to fill out supervised within-document event coreference

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Step 1: Read and understand the guidelines for supervised within-document event coreference.
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Step 2: Identify the events in the given document that need to be resolved.
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Step 3: Annotate the events using a consistent and agreed-upon annotation scheme.
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Step 4: Mark the coreference links between the events that refer to the same entity or occurrence.
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Step 5: Ensure that the annotations are accurate and follow the guidelines.
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Step 6: Review and revise the annotations if necessary.
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Step 7: Save the annotated document in the desired format.

Who needs supervised within-document event coreference?

01
Supervised within-document event coreference is needed by researchers and developers working on natural language processing (NLP) tasks such as information extraction, question answering, machine translation, sentiment analysis, and text summarization.
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It is particularly important for tasks involving event understanding and event-based applications.
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Entities or organizations involved in data annotation, such as annotation service providers or linguists, may also need supervised within-document event coreference to train machine learning models or evaluate system performance.
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Supervised within-document event coreference is a task in natural language processing that aims to identify and link together events mentioned in a text that refer to the same real-world occurrence.
Researchers and developers working on event coreference resolution tasks are required to apply supervised within-document event coreference.
Supervised within-document event coreference is typically filled out by training machine learning models on annotated datasets to identify and link events.
The purpose of supervised within-document event coreference is to improve the performance of event coreference resolution systems by leveraging labeled data for training.
Information such as event mentions, their attributes, and their relationships within a document must be reported on supervised within-document event coreference.
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