/NL2SQL-BERT

Content Enhanced BERT-based Text-to-SQL Generation

Primary LanguagePython

NL2SQL-BERT

LICENSE

Content Enhanced BERT-based Text-to-SQL Generation https://arxiv.org/abs/1910.07179

Run

1, Data prepare:

data_and_model/output_entity.py

2, Train and eval:

train.py

Results on BERT-Base-Uncased without EG

Model Dev
logical form
accuracy		 Dev
execution
accuracy		 Test
logical form
accuracy		 Test
execution
accuracy
SQLova 80.6 86.5 80.0 85.5
Our Methods 84.3 90.3 83.7 89.2

Data

One data look:

{
	"table_id": "1-1000181-1",
	"phase": 1,
	"question": "Tell me what the notes are for South Australia ",
	"question_tok": ["Tell", "me", "what", "the", "notes", "are", "for", "South", "Australia"],
	"sql": {
		"sel": 5,
		"conds": [
			[3, 0, "SOUTH AUSTRALIA"]
		],
		"agg": 0
	},
	"query": {
		"sel": 5,
		"conds": [
			[3, 0, "SOUTH AUSTRALIA"]
		],
		"agg": 0
	},
	"wvi_corenlp": [
		[7, 8]
	],
	"bertindex_knowledge": [0, 0, 0, 0, 4, 0, 0, 1, 3],
	"header_knowledge": [2, 0, 0, 2, 0, 1]
}

All origin data:

https://drive.google.com/file/d/1iJvsf38f16el58H4NPINQ7uzal5-V4v4

Trained model

https://drive.google.com/open?id=18MBm9qzobTBgWPZlpA2EErCQtsMhlTN2

Reference

https://github.com/naver/sqlova