GENERATING AND UTILIZING MODELS FOR LONG-RANGE EVENT RELATION EXTRACTION

    公开(公告)号:US20240378370A1

    公开(公告)日:2024-11-14

    申请号:US18316674

    申请日:2023-05-12

    Applicant: Adobe Inc.

    Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that generates a long-range event relation dataset by augmenting a digital document with a set of synthetic sentences. For example, the disclosed systems access a digital document from a short-range event relation dataset that includes an event pair. In some embodiments, the disclosed systems generate a set of synthetic sentences utilizing a generative language model for inserting within the digital document between the event pair to satisfy a long-range event relation threshold. In these or other embodiments, the disclosed systems generate a long-range event relation dataset by augmenting the digital document within the short-range event relation dataset to include the set of synthetic sentences. In certain cases, the disclosed systems generate an event relation extraction model to determine long-range event relations by learning model parameters for the event relation extraction model from the long-range event relation dataset.

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