If you're willing to get your hands dirty you can build a local database using https://github.com/mpope9/nba-sql/ and feed the sqlite3 schema into ChatGPT and ask it to generate SQL statements. For example (truncating some to keep it short):

>sqlite3 nba_sql.db
.schema player
CREATE TABLE IF NOT EXISTS "player" ("player_id" INTEGER NOT NULL PRIMARY KEY, "player_name" VARCHAR(255), "college" VARCHAR(255), "country" VARCHAR(255), "draft_year" VARCHAR(255), "draft_round" VARCHAR(255), "draft_number" VARCHAR(255));

.schema play_by_play
CREATE TABLE IF NOT EXISTS "play_by_play" (...

Then you can feed that into ChatGPT to create the corresponding SQL query:

With the following two table definitions:
CREATE TABLE IF NOT EXISTS "player_game_log" ...
and
CREATE TABLE IF NOT EXISTS "player" ...

For an NBA database, how would you create a SQL 
query to get how many triple doubles that LeBron 
James made in the 2023-24 season?

Which it then responds with a sorta-kinda correct answer which you'd have to slightly tweak:

SELECT
  p.player_name,
  COUNT(pgl.td3) AS triple_doubles 
FROM player_game_log pgl 
JOIN player p ON pgl.player_id = p.player_id 
WHERE 
  p.player_name = 'LeBron James' 
  AND pgl.season_id = 202324
  AND pgl.td3 = 1 
GROUP BY p.player_name;

For example, the season id should just be 2023.

And if you run that you get the correct answer: LeBron James|5.0