Papers › Sato: Contextual Semantic Type Detection in Tables

Sato: Contextual Semantic Type Detection in Tables

14 Nov 2019arXiv:1911.06311archive 2025-07-28

Dan Zhang, Yoshihiko Suhara, Jinfeng Li, Madelon Hulsebos, Çağatay Demiralp, Wang-Chiew Tan

Detecting the semantic types of data columns in relational tables is important for various data preparation and information retrieval tasks such as data cleaning, schema matching, data discovery, and semantic search. However, existing detection approaches either perform poorly with dirty data, support only a limited number of semantic types, fail to incorporate the table context of columns or rely on large sample sizes for training data. We introduce Sato, a hybrid machine learning model to automatically detect the semantic types of columns in tables, exploiting the signals from the context as well as the column values. Sato combines a deep learning model trained on a large-scale table corpus with topic modeling and structured prediction to achieve support-weighted and macro average F1 scores of 0.925 and 0.735, respectively, exceeding the state-of-the-art performance by a significant margin. We extensively analyze the overall and per-type performance of Sato, discussing how individual modeling components, as well as feature categories, contribute to its performance.

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str2bool megagonlabs/sato/utils.py official repository ran · violated contract Apache-2.0 (permissive) · 8605dc8a088f3db8 · report
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Tasks

Column Type AnnotationHybrid Machine LearningInformation RetrievalRetrievalStructured PredictionVocal Bursts Type Prediction

Datasets

Introduced by this paper, per the archive.

VizNet-Sato

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Column Type Annotation VizNet-Sato-Full Sato Macro-F1 75.6 #3 of 4 Archive leaderboard report
Column Type Annotation VizNet-Sato-Full Sato Weighted-F1 90.2 #3 of 4 Archive leaderboard report
Column Type Annotation VizNet-Sato-MultiColumn Sato Macro-F1 73.5 #2 of 2 Archive leaderboard report
Column Type Annotation VizNet-Sato-MultiColumn Sato Weighted-F1 92.5 #2 of 2 Archive leaderboard report

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