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- W4378084583 abstract "In this work, we present the first dataset, dataset, for performing event extraction from conversational email threads. To this end, we first proposed a new taxonomy covering 10 event types and 76 arguments in the email domain. Our final dataset includes $sim$4K emails annotated with $sim$9K event instances. To understand the task challenges, we conducted a series of experiments comparing two commonly-seen lines of approaches for event extraction, i.e., sequence labeling and generative end-to-end extraction (including few-shot GPT-3.5). Our results showed that the task of email event extraction is far from being addressed, due to challenges lying in, e.g., extracting non-continuous, shared trigger spans, extracting non-named entity arguments, and modeling the email conversational history. Our work thus suggests more investigations in this domain-specific event extraction task in the future.footnote{The source code and dataset can be obtained from url{https://github.com/salokr/Email-Event-Extraction}." @default.
- W4378084583 created "2023-05-25" @default.
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- W4378084583 date "2023-05-22" @default.
- W4378084583 modified "2023-09-28" @default.
- W4378084583 title "MAILEX: Email Event and Argument Extraction" @default.
- W4378084583 doi "https://doi.org/10.48550/arxiv.2305.13469" @default.
- W4378084583 hasPublicationYear "2023" @default.
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