# Refining Zero-Shot Text-to-SQL Benchmarks via Prompt Strategies with Large Language Models
## Appendix A Examples of Errors and Inconsistencies in the Original BIRD Dataset
### Summary of Identified Error Types in Original BIRD Dataset  
The following table summarizes the main categories of issues identified within the original BIRD dataset during our analysis, referencing examples discussed above. Whilethe paper estimates roughly 30% of pairs suffer from issues, this table categorizes the _types_ of problems encountered. **Question 477**  
Which of these artists have designed a card in the set Coldsnap, [PERSON], [PERSON] or Chippy? **Original Answer (Execution Time: 287 ms)**  
SELECT T1.artist FROM cards AS T1 INNER JOIN sets AS T2 ON T2.code = T1.setCode WHERE (T2.name = '[PERSON]' AND T1.artist = '[PERSON]') OR (T2.name = '[PERSON]' AND T1.artist = '[PERSON]') OR (T2.name = '[PERSON]' AND T1.artist = '[PERSON]') GROUP BY T1.artist  
**Newly Found Answer (Execution Time: 100 ms)**  
SELECT DISTINCT cards.artist FROM cards JOIN sets ON cards.setCode = sets.code WHERE cards.artist IN ('[PERSON]', '[PERSON]', '[PERSON]') AND sets.name = '[PERSON]'  
**Figure A1. ** Example of an overly complex SQL query from the BIRD dataset (Question 477). The question asks which of the listed artists ([PERSON], [PERSON], [PERSON]) designed a card in the Coldsnap set. The original answer uses repetitive conditions and a GROUP BY, taking 287 ms, while the simpler, more efficient alternative uses IN and DISTINCT, reducing execution time to 100 ms. This demonstrates a common mismatch where unnecessarily complex SQL is provided. **Question 94**  
List out the account numbers of female clients who are oldest and has lowest average salary calculate the gap between this lowest average salary with the highest average salary? **Original Answer**  
SELECT T1.account_id, ( SELECT MAX(A11) - MIN(A11) FROM district ) FROM account AS T1 INNER JOIN district AS T2 ON T1.district_id = T2.district_id WHERE T2.district_id = ( SELECT district_id FROM client WHERE gender = 'F' ORDER BY birth_date ASC LIMIT 1 ) ORDER BY T2.A11 DESC LIMIT 1  
**Error Analysis**  
The condition in the original answer (highlighted) restricts the query to the district of the single oldest female client. Since the average salary (A11) is uniform within a district, the question's intent--\"female clients who are oldest and has lowest average salary\"--implies identifying districts with the greatest average age of women and lowest salary, not just one client's district. This misalignment reflects ambiguous phrasing in the question leading to incorrect SQL logic. **Original Answer for Question 83**  
SELECT T2.City, COUNT(T2.CDSCode) FROM  
frm AS T1 INNER JOIN schools AS T2 ON  
T1.CDSCode = T2.CDSCode WHERE T2.Magnet  
AND T2.GSoffered = 'K-8' AND T1. 'NSLP  
Provision Status = 'Multiple Provision  
Types' GROUPS BY T2.City  
**Database Description for Magnet**  
\"The field is coded as follows:  
- Y = Magnet
- The school is a magnet school and/or offers  
a magnet program. - N = Not Magnet
- The school is not a magnet school and/or does not offer a magnet program. commonsense evidence:  
Note: Preschools and adult education centers do not contain a magnet school indicator.\"  
**Error Analysis**  
The condition T2.Magnet = 1 (highlighted in original answer)  
conflicts with the database description (highlighted in database description). The actual data in the 'Magnet' column uses '0' and '1', indicating the description's 'Y/N' coding is incorrect, leading to potential misreasoning by LLMs. **Figure A3. Example of inconsistency between database description and actual data from the BIRD dataset (Question 83). The original SQL assumes 'Magnet' is coded as '0' and '1' (using T2. Magnet = 1), while the database description specifies 'Y' and 'N', causing a mismatch. This error, noted in the analysis, can mislead LLMs into incorrect reasoning, reflecting a broader issue of data inconsistency in BIRD. **Question 880**  
[PERSON] was in the No. 853 race, what percent faster did he finish in the 853 rd race than the next race for the fastest lap speed?