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Register a new userText-to-SQL in the Wild: A Naturally-Occurring Dataset Based on Stack Exchange Data
Text-to-sql في البرية: مجموعة بيانات تحدث طبيعية تستند إلى بيانات تبادل المكدس
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تم جمع معظم مجموعات بيانات تحليل الدلالات المتاحة، والتي تتكون من أزواج من الكلام الطبيعي والنماذج المنطقية، فقط لغرض تدريب وتقييم أنظمة فهم اللغة الطبيعية.ونتيجة لذلك، فإنها لا تحتوي على أي من ثراء ومجموعة متنوعة من الكلام الطبيعية التي تحدث، حيث يسأل البشر عن البيانات التي يحتاجونها أو فضولها.في هذا العمل، نطلق سراح SEDE، مجموعة بيانات مع 12،023 أزواج من الكلام واستفسارات SQL التي تم جمعها من الاستخدام الحقيقي على موقع Stack Exchange.نظظ أن هذه الأزواج تحتوي على مجموعة متنوعة من التحديات في العالم الحقيقي والتي نادرا ما تنعكس حتى الآن في أي مجموعة بيانات تحليل دلالية أخرى، اقترح متري تقييم استنادا إلى مقارنة بنود الاستعلام الجزئي الأكثر ملاءمة لاستفسارات العالم الحقيقي، وإجراء تجاربمع خطوط أساس قوية، تظهر فجوة كبيرة بين الأداء على SEDE مقارنة مع مجموعات البيانات الشائعة الأخرى.
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.
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