{"url":"/dataset/parakweet-lab-s-email-intent-data-set","name":"Parakweet Lab's Email Intent Data Set","full_name":null,"description_markdown":"This resource contains training and test data for detecting \"intent\" sentences in email messages. This data comes from the Enron email corpus. Each labeled example is one sentence from an email.  We define \"intent\" here to correspond primarily to the categories \"request\" and \"propose\" in the paper:\r\n\r\nCohen, William W., Vitor R. Carvalho, and Tom M. Mitchell. \"Learning to Classify Email into``Speech Acts''.\" EMNLP. 2004.\r\n\r\nIn some cases, we also apply the positive label to some sentences from the \"commit\" category if they contain datetime, which makes them useful.\r\nDetecting the presence of intent in email is useful in many applications, e.g., machine mediation between human and email.\r\n\r\nTraining data: 4213 cases with 1631 positives\r\nTest data: 991 cases with 277 positives\r\n\r\nAlso see https://github.com/vseledkin/enron_intent_dataset_verified","description_withheld":null,"homepage":"https://github.com/ParakweetLabs/EmailIntentDataSet/wiki","introduced_date":null,"introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[],"tasks":[],"languages":[],"variants":["Parakweet Lab's Email Intent Data Set"],"data_loaders":[],"num_papers_in_archive":0,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}