@inproceedings{hazoom-etal-2021-text,
    title = "Text-to-{SQL} in the Wild: A Naturally-Occurring Dataset Based on Stack Exchange Data",
    author = "Hazoom, Moshe  and
      Malik, Vibhor  and
      Bogin, Ben",
    editor = "Lachmy, Royi  and
      Yao, Ziyu  and
      Durrett, Greg  and
      Gligoric, Milos  and
      Li, Junyi Jessy  and
      Mooney, Ray  and
      Neubig, Graham  and
      Su, Yu  and
      Sun, Huan  and
      Tsarfaty, Reut",
    booktitle = "Proceedings of the 1st Workshop on Natural Language Processing for Programming (NLP4Prog 2021)",
    month = aug,
    year = "2021",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-emnlp/2021.nlp4prog-1.9/",
    doi = "10.18653/v1/2021.nlp4prog-1.9",
    pages = "77--87",
    abstract = "Most available semantic parsing datasets, comprising of pairs of natural utterances and logical forms, were collected solely for the purpose of training and evaluation of natural language understanding systems. As a result, they do not contain any of the richness and variety of natural-occurring utterances, where humans ask about data they need or are curious about. In this work, we release SEDE, a dataset with 12,023 pairs of utterances and SQL queries collected from real usage on the Stack Exchange website. We show that these pairs contain a variety of real-world challenges which were rarely reflected so far in any other semantic parsing dataset, propose an evaluation metric based on comparison of partial query clauses that is more suitable for real-world queries, and conduct experiments with strong baselines, showing a large gap between the performance on SEDE compared to other common datasets."
}