Datasets:
Tasks:
Text2Text Generation
Modalities:
Text
Formats:
json
Languages:
English
Size:
1K - 10K
Tags:
schema-summarization
Update README.md
Browse files
README.md
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@@ -36,5 +36,6 @@ As the `xlangai/spider` and `richardr1126/spider-schema` are only labelled in en
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### Process
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So in order to create the summarized schema we proceded into several steps.
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First we go through every words in the orginal SQL query and see if it matches any column names in the original schema. And we add every column that we find this way.
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In order to leverage the
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### Source Data
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### Process
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So in order to create the summarized schema we proceded into several steps.
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First we go through every words in the orginal SQL query and see if it matches any column names in the original schema. And we add every column that we find this way.
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In order to leverage the '*' wildcard we automatically include the primary key of each table that is within the original SQL query
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### Source Data
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As explained above the natural question and SQL queries that answers this question are extracted from the `xlangai/spider` dataset and the databases schemas are extracted from the `richardr1126/spider-schema` dataset.
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