Papers with graph quality

2 papers
Holistic Evaluation of Automatic TimeML Annotators (2022.lrec-1)

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Challenge: TimeML is an annotation scheme for representing temporal information in texts.
Approach: They propose to combine eight metrics for holistic evaluation of TimeML graphs.
Outcome: The proposed system produces graphs with 1/3 of the time indeterminacy and 1/3 of gold standard . the proposed system is compared with four other systems and is a good fit for the proposed task.
ExplaGraphs: An Explanation Graph Generation Task for Structured Commonsense Reasoning (2021.emnlp-main)

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Challenge: Current commonsense-reasoning tasks are discriminative in nature, where a model answers a multiple-choice question for a certain context.
Approach: They propose a generative task that generates a commonsense-augmented graph for stance prediction by using a create-verify-and-refine graph collection framework.
Outcome: The proposed model is able to generate a graph that serves as non-trivial, complete, and unambiguous explanation for the predicted stance.

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