MAILEX: Email Event and Argument Extraction

• URL: http://arxiv.org/abs/2305.13469v2
• Date: Sat, 21 Oct 2023 02:15:22 GMT
• Title: MAILEX: Email Event and Argument Extraction
• Authors: Saurabh Srivastava, Gaurav Singh, Shou Matsumoto, Ali Raz, Paulo Costa, Joshua Poore, Ziyu Yao
• Abstract summary: We present the first dataset, MailEx, for performing event extraction from conversational email threads. Our dataset includes 1.5K email threads and 4K emails, which are annotated with totally 8K event instances.
• Score: 7.1087833991544125
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In this work, we present the first dataset, MailEx, 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 1.5K email threads and ~4K emails, which are annotated with totally ~8K event instances. To understand the task challenges, we conducted a series of experiments comparing three types of approaches, i.e., fine-tuned sequence labeling, fine-tuned generative extraction, and few-shot in-context learning. 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 future investigations in this domain-specific event extraction task.

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