Update README.md

README.md

@@ -1,6 +1,56 @@
 ---
 license: cc-by-sa-3.0
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+# sql-create-context-v2 Dataset
+
+## Overview
+
+The `sql-create-context-v2` dataset enhances the original dataset built from WikiSQL and Spider, focusing on text-to-SQL tasks with a special emphasis on reducing hallucination of column and table names. This version introduces a JSONL format for more efficient data processing and iteration, alongside a structured approach to representing SQL queries in the dataset entries.
+
+### Key Enhancements
+
+- **Dataset Format:** Transitioned to JSON Lines (JSONL) format for improved handling of large datasets and streamlined processing of individual records.
+- **Structured Query Representation:** Each SQL query answer is now encapsulated within an object keyed by `SQL_Query`, facilitating clearer separation between the query text and other metadata.
+
+## Cleansing and Augmentation
+
+Building upon the original dataset's cleansing and augmentation process, this version maintains the use of SQLGlot for parsing and inferring data types while introducing...
+
+## TODO
+
+- Convert queries and CREATE TABLE statements into different SQL dialects using SQLGlot.
+- Include references to the dialect in the question for better understanding.
+- Expand informative contexts beyond CREATE TABLE statements.
+- Enhance datatype parsing to address inconsistencies like numeric column names and strings as numbers.
+
+## Sample Entries
+
+```json
+{
+  "question": "Please show the themes of competitions with host cities having populations larger than 1000.",
+  "context": "CREATE TABLE city (City_ID VARCHAR, Population INTEGER); CREATE TABLE farm_competition (Theme VARCHAR, Host_city_ID VARCHAR)",
+  "answer": {"SQL_Query": "SELECT T2.Theme FROM city AS T1 JOIN farm_competition AS T2 ON T1.City_ID = T2.Host_city_ID WHERE T1.Population > 1000"}
+},
+{
+  "question": "Please show the different statuses of cities and the average population of cities with each status.",
+  "context": "CREATE TABLE city (Status VARCHAR, Population INTEGER)",
+  "answer": {"SQL_Query": "SELECT Status, AVG(Population) FROM city GROUP BY Status"}
+}
+
+Citing this Work
+If you use the sql-create-context-v2 dataset, please cite the following in addition to the original works:
+
+```
+@misc{sql-create-context-v2_2024,
+  title   = {sql-create-context-v2 Dataset},
+  author  = Rama Chetan Atmudi,
+  year    = {2024},
+  url     = {https://huggingface.co/datasets/ramachetan22/sql-create-context-v2},
+  note    = {Enhancements and modifications to the original sql-create-context dataset for improved usability and processing.}
+}
+```
+Datasets Used to Create This Dataset
+```
 @misc{b-mc2_2023_sql-create-context,
   title   = {sql-create-context Dataset},
   author  = {b-mc2}, 
@@ -8,8 +58,9 @@ license: cc-by-sa-3.0
   url     = {https://huggingface.co/datasets/b-mc2/sql-create-context},
   note    = {This dataset was created by modifying data from the following sources: \cite{zhongSeq2SQL2017, yu2018spider}.},
 }
-
-
+```
+```
+Datasets used to create this dataset
 @article{zhongSeq2SQL2017,
   author  = {Victor Zhong and Caiming Xiong and Richard Socher},
   title   = {Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning},
@@ -17,10 +68,12 @@ license: cc-by-sa-3.0
   volume  = {abs/1709.00103},
   year    = {2017}
 }
-
+```
+```
 @article{yu2018spider,
   title   = {Spider: A large-scale human-labeled dataset for complex and cross-domain semantic parsing and text-to-sql task},
   author  = {Yu, Tao and Zhang, Rui and Yang, Kai and Yasunaga, Michihiro and Wang, Dongxu and Li, Zifan and Ma, James and Li, Irene and Yao, Qingning and Roman, Shanelle and others},
   journal = {arXiv preprint arXiv:1809.08887},
   year    = {2018}
 }
+```