qid
stringlengths
5
5
task_type
stringclasses
1 value
has_intended_resolution
bool
1 class
db
stringclasses
6 values
question
stringlengths
33
189
gold_ambiguity_points
listlengths
1
5
gold_queries
listlengths
1
32
gold_intended_query_id
stringlengths
4
20
001-5
ambig
true
retails
Report the total revenue for each nation in 1995.
[ { "id": "A", "phrase": "total revenue", "type": "finite", "ambiguity_type": "semantic_computation", "interpretations": [ "before discount (Gross revenue)", "after discount (Net revenue)" ], "intended_interpretation_idx": 1 }, { "id": "B", "phrase": "total revenue"...
[ { "id": "GQRY-A.0-B.0-C.0-D.0", "query": "WITH revenue AS (\nSELECT n.n_nationkey,\nn.n_name,\nCOALESCE(SUM(l.l_extendedprice), 0) AS total_revenue\nFROM lineitem l\nJOIN orders o ON o.o_orderkey = l.l_orderkey\nJOIN customer c ON o.o_custkey = c.c_custkey\nJOIN nation n ON c.c_nationkey = n.n_nationkey\nWH...
GQRY-A.1-B.1-C.0-D.3
026-0
ambig
true
professional_basketball
For each team that Marcus Williams played for, compute his aggregate field goal percentage.
[ { "id": "A", "phrase": "Marcus Williams", "type": "finite", "ambiguity_type": "semantic_value", "interpretations": [ "Marcus Williams from University of Connecticut born in 1985", "Marcus Williams from University of Arizona born in 1986" ], "intended_interpretation_idx": 0 ...
[ { "id": "GQRY-A.0-B.0-C.0", "query": "SELECT\nt.tmID,\nt.name,\nCASE\nWHEN SUM(pt.fgAttempted) = 0 THEN 0\nELSE CAST(SUM(pt.fgMade) AS REAL) / SUM(pt.fgAttempted)\nEND as field_goal_percentage\nFROM players_teams pt\nJOIN players p ON pt.playerID = p.playerID\nJOIN teams t ON pt.tmID = t.tmID AND pt.year = ...
GQRY-A.0-B.1-C.0
036-0
ambig
true
github_repos
For each repository with a GPL license, count the number of merged PRs created in the period of 2022 and January 2023.
[ { "id": "A", "phrase": "GPL license", "type": "finite", "ambiguity_type": "semantic_value", "interpretations": [ "mainline GPL license (gpl-2.0 or gpl-3.0)", "all GPL variants including AGPL (agpl-3.0) and LGPL (lgpl-2.1 or lgpl-3.0)" ], "intended_interpretation_idx": 1 }, ...
[ { "id": "GQRY-A.0-B.0", "query": "WITH gpl_repos AS (\nSELECT grl.repo_name, grl.license\nFROM GITHUB_REPOS_LICENSES grl\nWHERE grl.license IN ('gpl-2.0', 'gpl-3.0')\n),\nall_events AS (\nSELECT * FROM YEAR_2022\nUNION ALL\nSELECT * FROM MONTH_202301\n),\nmerged_prs AS (\nSELECT\njson_extract(ae.repo, '$.na...
GQRY-A.1-B.0
058-2
ambig
true
financial
Compute the amount of deposits from December 1997 to end of 1998.
[ { "id": "A", "phrase": "amount", "type": "finite", "ambiguity_type": "semantic_computation", "interpretations": [ "the number of deposit transactions", "the total monetary value of deposits" ], "intended_interpretation_idx": 0 }, { "id": "B", "phrase": "deposits",...
[ { "id": "GQRY-A.0-B.0", "query": "SELECT COUNT(*)\nFROM trans\nWHERE operation = 'VKLAD'\nAND (date >= '1997-12-01' AND date < '1999-01-01');", "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sam...
GQRY-A.0-B.1
072-0
ambig
true
codebase_community
Find posts with many related posts.
[ { "id": "A", "phrase": "many", "type": "infinite", "ambiguity_type": "semantic_value", "parameter_name": "count_threshold", "parameter_dtype": "int", "parameter_sample_operators": [ ">", ">=" ], "parameter_sample_values": [ 10 ], "intended_parameter_oper...
[ { "id": "GQRY-B.0", "query": "SELECT p.Id, p.Title, COUNT(DISTINCT pl.RelatedPostId) AS RelatedCount\nFROM posts p\nJOIN postLinks pl ON p.Id = pl.PostId\nGROUP BY p.Id, p.Title\nHAVING COUNT(DISTINCT pl.RelatedPostId) > :count_threshold\nORDER BY RelatedCount DESC;", "parameter_names": [ "count_t...
GQRY-B.2
087-0
ambig
true
student_club
Which events had a low budget remaining or high spending on food or advertisement?
[ { "id": "A", "phrase": "low budget remaining", "type": "infinite", "ambiguity_type": "semantic_value", "parameter_name": "budget_remaining_threshold", "parameter_dtype": "int", "parameter_sample_operators": [ "<", "<=" ], "parameter_sample_values": [ 20 ], ...
[ { "id": "GQRY-B.0", "query": "WITH event_budget AS (\nSELECT\nlink_to_event AS event_id,\nSUM(remaining) AS total_remaining,\nSUM(CASE WHEN category = 'Food' THEN spent ELSE 0 END) AS food_spent,\nSUM(CASE WHEN category = 'Advertisement' THEN spent ELSE 0 END) AS adv_spent\nFROM budget\nGROUP BY link_to_eve...
GQRY-B.0
037-1
ambig
true
github_repos
List all repository names with many issues opened in 2022, provide the corresponding issue count and the license for each repository.
[ { "id": "A", "phrase": "many", "type": "infinite", "ambiguity_type": "semantic_value", "parameter_name": "issue_count_threshold", "parameter_dtype": "int", "parameter_sample_operators": [ ">", ">=" ], "parameter_sample_values": [ 7 ], "intended_parameter...
[ { "id": "GQRY-B.0", "query": "WITH issue_counts AS (\nSELECT\njson_extract(repo, '$.name') AS repo_name,\nCOUNT(DISTINCT json_extract(payload, '$.issue.id')) AS issues_opened\nFROM YEAR_2022\nWHERE type = 'IssuesEvent'\nAND json_extract(payload, '$.action') = 'opened'\nGROUP BY repo_name\nHAVING issues_open...
GQRY-B.0
002-4
ambig
true
retails
Count the number of suppliers that offer both air and rail shipping in America.
[ { "id": "A", "phrase": "suppliers that offer both air and rail shipping in America", "type": "finite", "ambiguity_type": "syntactic_computation", "interpretations": [ "suppliers that offer air and rail shipping to customers in America", "suppliers in America that offer air and rail s...
[ { "id": "GQRY-A.0-B.0-C.0", "query": "WITH usa_suppliers_with_air AS (\nSELECT DISTINCT l.l_suppkey\nFROM lineitem l\nJOIN orders o ON l.l_orderkey = o.o_orderkey\nJOIN customer c ON o.o_custkey = c.c_custkey\nJOIN nation n ON c.c_nationkey = n.n_nationkey\nWHERE n.n_name = 'UNITED STATES'\nAND l.l_shipmode...
GQRY-A.0-B.0-C.0
048-1
ambig
true
github_repos
Count the number of repository IDs in YEAR_2023 that have public events and also received a large number of pull requests.
[ { "id": "A", "phrase": "public events", "type": "finite", "ambiguity_type": "semantic_computation", "interpretations": [ "events with attribute public=1", "events of type 'PublicEvent'" ], "intended_interpretation_idx": 1 }, { "id": "B", "phrase": "received a larg...
[ { "id": "GQRY-A.0-B.0", "query": null, "parameter_names": [ "pr_count_threshold" ], "parameter_values": { "pr_count_threshold": 12 }, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { ...
GQRY-A.1-B.0
005-0
ambig
true
retails
Which part has the highest price?
[ { "id": "A", "phrase": "highest price", "type": "finite", "ambiguity_type": "semantic_computation", "interpretations": [ "highest absolute maximum price", "highest average price (aggregated over suppliers and orders)" ], "intended_interpretation_idx": 1 }, { "id": "B"...
[ { "id": "GQRY-A.0-B.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "p_partkey": 27602, "p_name": "powder tan cornsilk...
GQRY-A.1-B.1
066-0
ambig
true
financial
Show the average age and number of male clients by region, assuming the current date is August 1st, 2025.
[ { "id": "A", "phrase": "average age and number of male clients", "type": "finite", "ambiguity_type": "syntactic_computation", "interpretations": [ "average age of all clients and number of male clients", "average age of male clients and number of male clients" ], "intended_in...
[ { "id": "GQRY-A.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "region": "Prague", "avg_age": 71.431372549, ...
GQRY-A.0
096-0
ambig
true
student_club
List all members from New York who have signed up for events in September or October 1st in 2019 and display their major, phone number and the event name.
[ { "id": "A", "phrase": "New York", "type": "finite", "ambiguity_type": "semantic_column", "interpretations": [ "New York City", "New York County", "New York State" ], "intended_interpretation_idx": 0 }, { "id": "B", "phrase": "September or October 1st", ...
[ { "id": "GQRY-A.0-B.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "first_name": "Luisa", "last_name": "Guidi", ...
GQRY-A.0-B.0
042-0
ambig
true
github_repos
Count the total number of Wiki pages updated in the last month of 2022 and 2023.
[ { "id": "A", "phrase": "Wiki pages updated", "type": "finite", "ambiguity_type": "semantic_value", "interpretations": [ "Wiki pages created", "Wiki pages edited", "Wiki pages created or edited" ], "intended_interpretation_idx": 2 }, { "id": "B", "phrase": "l...
[ { "id": "GQRY-A.0-B.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "total_wiki_pages_updated": 0 } ], ...
GQRY-A.2-B.1
096-4
ambig
true
student_club
List all members from New York who have signed up for events in September or October 1st in 2019 and display their major, phone number and the event name.
[ { "id": "A", "phrase": "New York", "type": "finite", "ambiguity_type": "semantic_column", "interpretations": [ "New York City", "New York County", "New York State" ], "intended_interpretation_idx": 2 }, { "id": "B", "phrase": "September or October 1st", ...
[ { "id": "GQRY-A.0-B.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "first_name": "Luisa", "last_name": "Guidi", ...
GQRY-A.2-B.0
056-0
ambig
true
github_repos
Count the number of 2022 public events whose actor is also the actor of more than 5 events in 2022.
[ { "id": "A", "phrase": "public events", "type": "finite", "ambiguity_type": "semantic_computation", "interpretations": [ "events with attribute public=1", "events of type 'PublicEvent'" ], "intended_interpretation_idx": 0 } ]
[ { "id": "GQRY-A.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "COUNT(*)": 455197 } ], "num_rows": ...
GQRY-A.0
090-1
ambig
true
student_club
List all events attended by members in Albany, including their name and location.
[ { "id": "A", "phrase": "Albany", "type": "finite", "ambiguity_type": "semantic_computation", "interpretations": [ "Albany city, Vermont", "Albany city, New York", "Albany city, Georgia", "Albany city, Kentucky", "Albany city, Ohio", "Albany city, Indiana", ...
[ { "id": "GQRY-A.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [], "num_rows": 0 }, "parquet_base64": "UEFSMRUEFQAVAkwVABUAEgAAABUEFQAV...
GQRY-A.1
008-4
ambig
true
retails
Identify the manufacturer that contributed the highest profit during the last quarter of 1994. Show the manufacturer and the profit.
[ { "id": "A", "phrase": "highest profit", "type": "finite", "ambiguity_type": "semantic_computation", "interpretations": [ "include returned items", "exclude returned items" ], "intended_interpretation_idx": 1 }, { "id": "B", "phrase": "during the last quarter of 1...
[ { "id": "GQRY-A.0-B.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "p_mfgr": "Manufacturer#3", "profit": 1098055932.9...
GQRY-A.1-B.3
062-1
ambig
true
financial
For each bank in the database, show the total sum of household or insurance payments in 1997 and 1998, grouped accordingly.
[ { "id": "A", "phrase": "grouped accordingly", "type": "finite", "ambiguity_type": "semantic_computation", "interpretations": [ "group by bank only", "group by bank and payment type", "group by bank and year", "group by bank, payment type, year" ], "intended_interp...
[ { "id": "GQRY-A.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "bank": "AB", "total_amount": 24060373 }, ...
GQRY-A.3
070-0
ambig
true
financial
What is the total number of weekly-fee accounts in districts with many large municipalities?
[ { "id": "A", "phrase": "many", "type": "infinite", "ambiguity_type": "semantic_value", "parameter_name": "municipality_threshold", "parameter_dtype": "int", "parameter_sample_operators": [ ">", ">=" ], "parameter_sample_values": [ 8 ], "intended_paramete...
[ { "id": "GQRY-B.0", "query": null, "parameter_names": [ "municipality_threshold" ], "parameter_values": { "municipality_threshold": 8 }, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { ...
GQRY-B.1
024-0
ambig
true
retails
Show large orders placed in February 1996.
[ { "id": "A", "phrase": "large orders", "type": "finite", "ambiguity_type": "semantic_computation", "interpretations": [ "orders with high total price", "orders with large number of line items", "orders with large total quantity of parts" ], "intended_interpretation_idx"...
[ { "id": "GQRY-A.0", "query": null, "parameter_names": [ "large_threshold" ], "parameter_values": { "large_threshold": 250 }, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "o_or...
GQRY-A.0
042-2
ambig
true
github_repos
Count the total number of Wiki pages updated in the last month of 2022 and 2023.
[ { "id": "A", "phrase": "Wiki pages updated", "type": "finite", "ambiguity_type": "semantic_value", "interpretations": [ "Wiki pages created", "Wiki pages edited", "Wiki pages created or edited" ], "intended_interpretation_idx": 0 }, { "id": "B", "phrase": "l...
[ { "id": "GQRY-A.0-B.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "total_wiki_pages_updated": 0 } ], ...
GQRY-A.0-B.1
064-0
ambig
true
financial
Find the accounts with high transaction value related to insurance payments and display the corresponding value.
[ { "id": "A", "phrase": "high transaction value", "type": "finite", "ambiguity_type": "semantic_computation", "interpretations": [ "high single transaction value", "high total transaction value", "high average transaction value" ], "intended_interpretation_idx": 1 }, ...
[ { "id": "GQRY-A.0", "query": null, "parameter_names": [ "amount_threshold" ], "parameter_values": { "amount_threshold": 5000 }, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "a...
GQRY-A.1
079-0
ambig
true
codebase_community
Identify tags used in many posts in early years.
[ { "id": "A", "phrase": "many posts", "type": "infinite", "ambiguity_type": "semantic_value", "parameter_name": "count_threshold", "parameter_dtype": "int", "parameter_sample_operators": [ ">", ">=" ], "parameter_sample_values": [ 286 ], "intended_paramet...
[ { "id": "GQRY", "query": null, "parameter_names": [ "date_threshold", "count_threshold" ], "parameter_values": { "date_threshold": "2012-02-29", "count_threshold": 286 }, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { ...
GQRY
064-1
ambig
true
financial
Find the accounts with high transaction value related to insurance payments and display the corresponding value.
[ { "id": "A", "phrase": "high transaction value", "type": "finite", "ambiguity_type": "semantic_computation", "interpretations": [ "high single transaction value", "high total transaction value", "high average transaction value" ], "intended_interpretation_idx": 2 }, ...
[ { "id": "GQRY-A.0", "query": null, "parameter_names": [ "amount_threshold" ], "parameter_values": { "amount_threshold": 5000 }, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "a...
GQRY-A.2
046-0
ambig
true
github_repos
In the January 2023 table, find all repo names that were forked or had issues opened and have public events.
[ { "id": "A", "phrase": "forked or had issues opened and have public events", "type": "finite", "ambiguity_type": "syntactic_computation", "interpretations": [ "(were forked OR had issues opened) AND (have public events in January 2023)", "(were forked) OR (had issues opened AND have ...
[ { "id": "GQRY-A.0-B.0-C.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "repo_name": "unifyai/ivy" }, { ...
GQRY-A.1-B.1-C.0
062-2
ambig
true
financial
For each bank in the database, show the total sum of household or insurance payments in 1997 and 1998, grouped accordingly.
[ { "id": "A", "phrase": "grouped accordingly", "type": "finite", "ambiguity_type": "semantic_computation", "interpretations": [ "group by bank only", "group by bank and payment type", "group by bank and year", "group by bank, payment type, year" ], "intended_interp...
[ { "id": "GQRY-A.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "bank": "AB", "total_amount": 24060373 }, ...
GQRY-A.1
001-1
ambig
true
retails
Report the total revenue for each nation in 1995.
[ { "id": "A", "phrase": "total revenue", "type": "finite", "ambiguity_type": "semantic_computation", "interpretations": [ "before discount (Gross revenue)", "after discount (Net revenue)" ], "intended_interpretation_idx": 0 }, { "id": "B", "phrase": "total revenue"...
[ { "id": "GQRY-A.0-B.0-C.0-D.0", "query": "WITH revenue AS (\nSELECT n.n_nationkey,\nn.n_name,\nCOALESCE(SUM(l.l_extendedprice), 0) AS total_revenue\nFROM lineitem l\nJOIN orders o ON o.o_orderkey = l.l_orderkey\nJOIN customer c ON o.o_custkey = c.c_custkey\nJOIN nation n ON c.c_nationkey = n.n_nationkey\nWH...
GQRY-A.0-B.0-C.0-D.0
032-0
ambig
true
professional_basketball
List tall players that have played for NBA teams from Los Angeles.
[ { "id": "A", "phrase": "tall players", "type": "infinite", "ambiguity_type": "semantic_value", "parameter_name": "height_threshold", "parameter_dtype": "int", "parameter_sample_operators": [ ">", ">=" ], "parameter_sample_values": [ 84 ], "intended_param...
[ { "id": "GQRY-B.0", "query": null, "parameter_names": [ "height_threshold" ], "parameter_values": { "height_threshold": 84 }, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "pla...
GQRY-B.1
064-2
ambig
true
financial
Find the accounts with high transaction value related to insurance payments and display the corresponding value.
[ { "id": "A", "phrase": "high transaction value", "type": "finite", "ambiguity_type": "semantic_computation", "interpretations": [ "high single transaction value", "high total transaction value", "high average transaction value" ], "intended_interpretation_idx": 0 }, ...
[ { "id": "GQRY-A.0", "query": null, "parameter_names": [ "amount_threshold" ], "parameter_values": { "amount_threshold": 5000 }, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "a...
GQRY-A.0
093-4
ambig
true
student_club
Show the number of members for each region in the Morgan County .
[ { "id": "A", "phrase": "region", "type": "finite", "ambiguity_type": "semantic_column", "interpretations": [ "zip code", "city" ], "intended_interpretation_idx": 1 }, { "id": "B", "phrase": "Morgan County", "type": "finite", "ambiguity_type": "semantic_val...
[ { "id": "GQRY-A.0-B.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "zip_code": 25411, "member_count": 0 }...
GQRY-A.1-B.9
009-0
ambig
true
retails
List the customer who made the highest number of purchases using rail shipping.
[ { "id": "A", "phrase": "number of purchases using rail shipping", "type": "finite", "ambiguity_type": "semantic_computation", "interpretations": [ "number of orders containing at least one line item shipped by rail", "number of line items shipped by rail", "total quantity shipp...
[ { "id": "GQRY-A.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "c_custkey": 63035, "c_name": "Customer#000063035", ...
GQRY-A.1
097-4
ambig
true
student_club
Find the total funds allocated for food and advertisement for all events attended by members in New York.
[ { "id": "A", "phrase": "total funds allocated for food and advertisement", "type": "finite", "ambiguity_type": "syntactic_computation", "interpretations": [ "total funds for food and advertisement (single number)", "total funds for food and total funds for advertisement (two separate...
[ { "id": "GQRY-A.0-B.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "total_funds": 1795 } ], "num_ro...
GQRY-A.1-B.0
084-0
ambig
true
codebase_community
List the posts with negative comments authored by MYaseen208.
[ { "id": "A", "phrase": "authored by MYaseen208", "type": "finite", "ambiguity_type": "syntactic_table", "interpretations": [ "comments authored by MYaseen208", "posts authored by MYaseen208" ], "intended_interpretation_idx": 0 } ]
[ { "id": "GQRY-A.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "Id": 8787, "Title": "Generalized linear latent and mi...
GQRY-A.0
026-4
ambig
true
professional_basketball
For each team that Marcus Williams played for, compute his aggregate field goal percentage.
[ { "id": "A", "phrase": "Marcus Williams", "type": "finite", "ambiguity_type": "semantic_value", "interpretations": [ "Marcus Williams from University of Connecticut born in 1985", "Marcus Williams from University of Arizona born in 1986" ], "intended_interpretation_idx": 1 ...
[ { "id": "GQRY-A.0-B.0-C.0", "query": "SELECT\nt.tmID,\nt.name,\nCASE\nWHEN SUM(pt.fgAttempted) = 0 THEN 0\nELSE CAST(SUM(pt.fgMade) AS REAL) / SUM(pt.fgAttempted)\nEND as field_goal_percentage\nFROM players_teams pt\nJOIN players p ON pt.playerID = p.playerID\nJOIN teams t ON pt.tmID = t.tmID AND pt.year = ...
GQRY-A.1-B.0-C.1
044-1
ambig
true
github_repos
Find the most active organization in 2023.
[ { "id": "A", "phrase": "most active organization", "type": "finite", "ambiguity_type": "semantic_computation", "interpretations": [ "organization with the highest total number of events", "organization with the highest number of repositories that generated events", "organizatio...
[ { "id": "GQRY-A.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "org_id": 8158177, "event_count": 42493 } ...
GQRY-A.0
076-3
ambig
true
codebase_community
How many users have received mostly positive scores for posts they contributed?
[ { "id": "A", "phrase": "mostly", "type": "infinite", "ambiguity_type": "semantic_value", "parameter_name": "percentage_threshold", "parameter_dtype": "float", "parameter_sample_operators": [ ">", ">=" ], "parameter_sample_values": [ 0.8 ], "intended_para...
[ { "id": "GQRY-B.0-C.0", "query": null, "parameter_names": [ "percentage_threshold" ], "parameter_values": { "percentage_threshold": 0.8 }, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { ...
GQRY-B.1-C.0
071-0
ambig
true
financial
Show the district name and average salary for each district with the lowest number of urban residents and entrepreneurs.
[ { "id": "A", "phrase": "each district with the lowest number of urban residents and entrepreneurs", "type": "finite", "ambiguity_type": "syntactic_computation", "interpretations": [ "(each district with the lowest number of urban residents) and (each district with the lowest number of entr...
[ { "id": "GQRY-A.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "district_name": "Rokycany", "average_salary": 8843, ...
GQRY-A.0
001-6
ambig
true
retails
Report the total revenue for each nation in 1995.
[ { "id": "A", "phrase": "total revenue", "type": "finite", "ambiguity_type": "semantic_computation", "interpretations": [ "before discount (Gross revenue)", "after discount (Net revenue)" ], "intended_interpretation_idx": 0 }, { "id": "B", "phrase": "total revenue"...
[ { "id": "GQRY-A.0-B.0-C.0-D.0", "query": "WITH revenue AS (\nSELECT n.n_nationkey,\nn.n_name,\nCOALESCE(SUM(l.l_extendedprice), 0) AS total_revenue\nFROM lineitem l\nJOIN orders o ON o.o_orderkey = l.l_orderkey\nJOIN customer c ON o.o_custkey = c.c_custkey\nJOIN nation n ON c.c_nationkey = n.n_nationkey\nWH...
GQRY-A.0-B.0-C.1-D.0
027-0
ambig
true
professional_basketball
List all teams with low points allowed from the Western conference that have made the playoffs.
[ { "id": "A", "phrase": "low points allowed", "type": "finite", "ambiguity_type": "semantic_computation", "interpretations": [ "low total points allowed", "low points allowed per season", "low points allowed per game" ], "intended_interpretation_idx": 2 }, { "id"...
[ { "id": "GQRY-A.0-C.0", "query": "SELECT t1.tmID, t1.name, SUM(t1.d_pts) AS total_points_allowed\nFROM teams t1\nWHERE t1.tmID IN (\nSELECT DISTINCT tmID\nFROM teams\nWHERE confID = 'WC' AND playoff IS NOT NULL\n)\nGROUP BY t1.tmID, t1.name\nHAVING SUM(t1.d_pts) < :points_allowed_threshold\nORDER BY SUM(t1....
GQRY-A.2-C.0
082-0
ambig
true
codebase_community
For each user in Portland, show the number of posts they have created.
[ { "id": "A", "phrase": "Portland", "type": "finite", "ambiguity_type": "semantic_value", "interpretations": [ "Portland, Oregon", "Portland, Maine" ], "intended_interpretation_idx": 1 } ]
[ { "id": "GQRY-A.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "UserId": 38, "DisplayName": "EAMann", "...
GQRY-A.1
092-2
ambig
true
student_club
Find the total funds allocated for speaker gifts and t-shirts for each event attended by members in Georgetown in South Carolina.
[ { "id": "A", "phrase": "total funds allocated for speaker gifts and t-shirts", "type": "finite", "ambiguity_type": "syntactic_computation", "interpretations": [ "total funds for speaker gifts and t-shirts (single number)", "total funds for speaker gifts and total funds for t-shirts (...
[ { "id": "GQRY-A.0-B.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "event_id": "recEVTik3MlqbvLFi", "event_name": "Oc...
GQRY-A.1-B.1
072-1
ambig
true
codebase_community
Find posts with many related posts.
[ { "id": "A", "phrase": "many", "type": "infinite", "ambiguity_type": "semantic_value", "parameter_name": "count_threshold", "parameter_dtype": "int", "parameter_sample_operators": [ ">", ">=" ], "parameter_sample_values": [ 10 ], "intended_parameter_oper...
[ { "id": "GQRY-B.0", "query": "SELECT p.Id, p.Title, COUNT(DISTINCT pl.RelatedPostId) AS RelatedCount\nFROM posts p\nJOIN postLinks pl ON p.Id = pl.PostId\nGROUP BY p.Id, p.Title\nHAVING COUNT(DISTINCT pl.RelatedPostId) > :count_threshold\nORDER BY RelatedCount DESC;", "parameter_names": [ "count_t...
GQRY-B.0
099-5
ambig
true
student_club
For each event label, show the total amount spent by events with food and gifts. Return the result in (label, total_amount) format.
[ { "id": "A", "phrase": "event label", "type": "finite", "ambiguity_type": "semantic_column", "interpretations": [ "event type (event.type)", "event status (event.status)" ], "intended_interpretation_idx": 0 }, { "id": "B", "phrase": "total amount spent", "type...
[ { "id": "GQRY-A.0-B.0-C.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "event_status": "Closed", "total_spent": 1562....
GQRY-A.0-B.1-C.1
031-0
ambig
true
professional_basketball
Count the number of people that have coached for Atlanta.
[ { "id": "A", "phrase": "Atlanta", "type": "finite", "ambiguity_type": "semantic_value", "interpretations": [ "Atlanta Hawks (tmID = 'ATL')", "Atlanta Crackers (tmID = 'ATC')" ], "intended_interpretation_idx": 0 } ]
[ { "id": "GQRY-A.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "COUNT(DISTINCT coachID)": 12 } ], "...
GQRY-A.0
013-1
ambig
true
retails
Show the total quantity and total final charge of all items shipped by mail or with discount greater than 5% and returned.
[ { "id": "A", "phrase": "items shipped by mail or with discount greater than 5% and returned", "type": "finite", "ambiguity_type": "syntactic_computation", "interpretations": [ "items (shipped by mail) OR (with discount greater than 5% AND returned).", "items (shipped by mail OR with ...
[ { "id": "GQRY-A.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "total_quantity": 22960669, "total_charge": 3368181931...
GQRY-A.0
042-1
ambig
true
github_repos
Count the total number of Wiki pages updated in the last month of 2022 and 2023.
[ { "id": "A", "phrase": "Wiki pages updated", "type": "finite", "ambiguity_type": "semantic_value", "interpretations": [ "Wiki pages created", "Wiki pages edited", "Wiki pages created or edited" ], "intended_interpretation_idx": 2 }, { "id": "B", "phrase": "l...
[ { "id": "GQRY-A.0-B.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "total_wiki_pages_updated": 0 } ], ...
GQRY-A.2-B.0
047-0
ambig
true
github_repos
Count the number of forks in public repositories in March.
[ { "id": "A", "phrase": "March", "type": "finite", "ambiguity_type": "semantic_table", "interpretations": [ "March 2022", "March 2023", "March in both 2022 and 2023" ], "intended_interpretation_idx": 2 } ]
[ { "id": "GQRY-A.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "COUNT(*)": 63 } ], "num_rows": 1 ...
GQRY-A.2
002-5
ambig
true
retails
Count the number of suppliers that offer both air and rail shipping in America.
[ { "id": "A", "phrase": "suppliers that offer both air and rail shipping in America", "type": "finite", "ambiguity_type": "syntactic_computation", "interpretations": [ "suppliers that offer air and rail shipping to customers in America", "suppliers in America that offer air and rail s...
[ { "id": "GQRY-A.0-B.0-C.0", "query": "WITH usa_suppliers_with_air AS (\nSELECT DISTINCT l.l_suppkey\nFROM lineitem l\nJOIN orders o ON l.l_orderkey = o.o_orderkey\nJOIN customer c ON o.o_custkey = c.c_custkey\nJOIN nation n ON c.c_nationkey = n.n_nationkey\nWHERE n.n_name = 'UNITED STATES'\nAND l.l_shipmode...
GQRY-A.0-B.1-C.0
058-4
ambig
true
financial
Compute the amount of deposits from December 1997 to end of 1998.
[ { "id": "A", "phrase": "amount", "type": "finite", "ambiguity_type": "semantic_computation", "interpretations": [ "the number of deposit transactions", "the total monetary value of deposits" ], "intended_interpretation_idx": 0 }, { "id": "B", "phrase": "deposits",...
[ { "id": "GQRY-A.0-B.0", "query": "SELECT COUNT(*)\nFROM trans\nWHERE operation = 'VKLAD'\nAND (date >= '1997-12-01' AND date < '1999-01-01');", "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sam...
GQRY-A.0-B.2
044-0
ambig
true
github_repos
Find the most active organization in 2023.
[ { "id": "A", "phrase": "most active organization", "type": "finite", "ambiguity_type": "semantic_computation", "interpretations": [ "organization with the highest total number of events", "organization with the highest number of repositories that generated events", "organizatio...
[ { "id": "GQRY-A.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "org_id": 8158177, "event_count": 42493 } ...
GQRY-A.1
082-1
ambig
true
codebase_community
For each user in Portland, show the number of posts they have created.
[ { "id": "A", "phrase": "Portland", "type": "finite", "ambiguity_type": "semantic_value", "interpretations": [ "Portland, Oregon", "Portland, Maine" ], "intended_interpretation_idx": 0 } ]
[ { "id": "GQRY-A.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "UserId": 38, "DisplayName": "EAMann", "...
GQRY-A.0
008-1
ambig
true
retails
Identify the manufacturer that contributed the highest profit during the last quarter of 1994. Show the manufacturer and the profit.
[ { "id": "A", "phrase": "highest profit", "type": "finite", "ambiguity_type": "semantic_computation", "interpretations": [ "include returned items", "exclude returned items" ], "intended_interpretation_idx": 0 }, { "id": "B", "phrase": "during the last quarter of 1...
[ { "id": "GQRY-A.0-B.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "p_mfgr": "Manufacturer#3", "profit": 1098055932.9...
GQRY-A.0-B.0
030-3
ambig
true
professional_basketball
Compute the total post-season offensive rebounds and games played in their career for each player born in Oklahoma.
[ { "id": "A", "phrase": "total post-season offensive rebounds and games played", "type": "finite", "ambiguity_type": "syntactic_column", "interpretations": [ "total post-season offensive rebounds and post-season games played", "total post-season offensive rebounds and all games played...
[ { "id": "GQRY-A.0-B.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "playerID": "beaslch01", "firstName": "Charles", ...
GQRY-A.0-B.1
058-3
ambig
true
financial
Compute the amount of deposits from December 1997 to end of 1998.
[ { "id": "A", "phrase": "amount", "type": "finite", "ambiguity_type": "semantic_computation", "interpretations": [ "the number of deposit transactions", "the total monetary value of deposits" ], "intended_interpretation_idx": 1 }, { "id": "B", "phrase": "deposits",...
[ { "id": "GQRY-A.0-B.0", "query": "SELECT COUNT(*)\nFROM trans\nWHERE operation = 'VKLAD'\nAND (date >= '1997-12-01' AND date < '1999-01-01');", "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sam...
GQRY-A.1-B.0
029-4
ambig
true
professional_basketball
What is Charles Smith's best true shooting percentage in a season in his career?
[ { "id": "A", "phrase": "Charles Smith", "type": "finite", "ambiguity_type": "semantic_value", "interpretations": [ "Charles Smith from University of Pittsburgh born on July 16, 1965", "Charles Smith from Georgetown University born on November 29, 1967", "Charles Smith from Marq...
[ { "id": "GQRY-A.0-B.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "year": 1989, "true_shooting_percentage": 0.588896...
GQRY-A.0-B.2
060-5
ambig
true
financial
Count the number of young clients with significant loans and large transactions for each area.
[ { "id": "A", "phrase": "Count the number of young clients with significant loans and large transactions", "type": "finite", "ambiguity_type": "semantic_computation", "interpretations": [ "count clients with either significant loans or large transactions ('and' means UNION)", "count c...
[ { "id": "GQRY-A.0-E.0", "query": null, "parameter_names": [ "loan_amount_threshold", "birth_date_threshold", "transaction_amount_threshold", "birth_date_threshold" ], "parameter_values": { "loan_amount_threshold": 12000, "birth_date_threshold": "1960-01-01", ...
GQRY-A.1-E.0
039-0
ambig
true
github_repos
Show the top 20 user names that contribute most events in January 2023 and 2022.
[ { "id": "A", "phrase": "January 2023 and 2022", "type": "finite", "ambiguity_type": "syntactic_table", "interpretations": [ "January 2023 and January 2022", "January 2023 and the entire 2022" ], "intended_interpretation_idx": 0 } ]
[ { "id": "GQRY-A.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "user": "LombiqBot", "event_count": 23522 ...
GQRY-A.0
018-0
ambig
true
retails
Count the number of customers that have used air shipping.
[ { "id": "A", "phrase": "air shipping", "type": "finite", "ambiguity_type": "semantic_value", "interpretations": [ "ship mode is AIR", "ship mode is AIR or REG AIR" ], "intended_interpretation_idx": 1 } ]
[ { "id": "GQRY-A.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "COUNT(DISTINCT c.c_custkey)": 88988 } ], ...
GQRY-A.1
097-1
ambig
true
student_club
Find the total funds allocated for food and advertisement for all events attended by members in New York.
[ { "id": "A", "phrase": "total funds allocated for food and advertisement", "type": "finite", "ambiguity_type": "syntactic_computation", "interpretations": [ "total funds for food and advertisement (single number)", "total funds for food and total funds for advertisement (two separate...
[ { "id": "GQRY-A.0-B.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "total_funds": 1795 } ], "num_ro...
GQRY-A.1-B.1
069-0
ambig
true
financial
For each account frequency category, show the most recent activity date.
[ { "id": "A", "phrase": "activity date", "type": "finite", "ambiguity_type": "semantic_table", "interpretations": [ "account creation date", "card issued date", "loan date", "transaction date", "any of account, loan, card, or transaction dates" ], "intended_i...
[ { "id": "GQRY-A.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "frequency": "POPLATEK MESICNE", "most_recent_status_u...
GQRY-A.1
002-0
ambig
true
retails
Count the number of suppliers that offer both air and rail shipping in America.
[ { "id": "A", "phrase": "suppliers that offer both air and rail shipping in America", "type": "finite", "ambiguity_type": "syntactic_computation", "interpretations": [ "suppliers that offer air and rail shipping to customers in America", "suppliers in America that offer air and rail s...
[ { "id": "GQRY-A.0-B.0-C.0", "query": "WITH usa_suppliers_with_air AS (\nSELECT DISTINCT l.l_suppkey\nFROM lineitem l\nJOIN orders o ON l.l_orderkey = o.o_orderkey\nJOIN customer c ON o.o_custkey = c.c_custkey\nJOIN nation n ON c.c_nationkey = n.n_nationkey\nWHERE n.n_name = 'UNITED STATES'\nAND l.l_shipmode...
GQRY-A.0-B.0-C.1
030-2
ambig
true
professional_basketball
Compute the total post-season offensive rebounds and games played in their career for each player born in Oklahoma.
[ { "id": "A", "phrase": "total post-season offensive rebounds and games played", "type": "finite", "ambiguity_type": "syntactic_column", "interpretations": [ "total post-season offensive rebounds and post-season games played", "total post-season offensive rebounds and all games played...
[ { "id": "GQRY-A.0-B.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "playerID": "beaslch01", "firstName": "Charles", ...
GQRY-A.1-B.0
045-2
ambig
true
github_repos
What is the highest number of issues opened by a single repository (identified by repo ID) in Q3? Use the YEAR_* tables.
[ { "id": "A", "phrase": "issues opened", "type": "finite", "ambiguity_type": "semantic_value", "interpretations": [ "issues created", "issues created or reopened" ], "intended_interpretation_idx": 0 }, { "id": "B", "phrase": "Q3", "type": "finite", "ambigui...
[ { "id": "GQRY-A.0-B.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "MAX(issues_opened)": 67 } ], "n...
GQRY-A.0-B.1
035-1
ambig
true
professional_basketball
Count the number of people who played or coached in the NBA finals in the 1990s.
[ { "id": "A", "phrase": "played or coached in the NBA finals in the 1990s", "type": "finite", "ambiguity_type": "syntactic_computation", "interpretations": [ "(played in the 1990s) or (coached in the NBA finals in the 1990s)", "(played or coached) in the NBA finals in the 1990s." ...
[ { "id": "GQRY-A.0-B.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "COUNT(DISTINCT personID)": 1027 } ], ...
GQRY-A.1-B.1
096-1
ambig
true
student_club
List all members from New York who have signed up for events in September or October 1st in 2019 and display their major, phone number and the event name.
[ { "id": "A", "phrase": "New York", "type": "finite", "ambiguity_type": "semantic_column", "interpretations": [ "New York City", "New York County", "New York State" ], "intended_interpretation_idx": 2 }, { "id": "B", "phrase": "September or October 1st", ...
[ { "id": "GQRY-A.0-B.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "first_name": "Luisa", "last_name": "Guidi", ...
GQRY-A.2-B.1
012-0
ambig
true
retails
List all suppliers with a high balance.
[ { "id": "A", "phrase": "high balance", "type": "infinite", "ambiguity_type": "semantic_value", "parameter_name": "balance_threshold", "parameter_dtype": "int", "parameter_sample_operators": [ ">", ">=" ], "parameter_sample_values": [ 8500, 9000, 9500...
[ { "id": "GQRY", "query": null, "parameter_names": [ "balance_threshold" ], "parameter_values": { "balance_threshold": 8500 }, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "s_s...
GQRY
049-1
ambig
true
github_repos
List the active PR contributors in 2022.
[ { "id": "A", "phrase": "active", "type": "infinite", "ambiguity_type": "semantic_value", "parameter_name": "pr_count_threshold", "parameter_dtype": "int", "parameter_sample_operators": [ ">", ">=" ], "parameter_sample_values": [ 100 ], "intended_paramete...
[ { "id": "GQRY-B.0", "query": null, "parameter_names": [ "pr_count_threshold" ], "parameter_values": { "pr_count_threshold": 100 }, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { ...
GQRY-B.0
031-1
ambig
true
professional_basketball
Count the number of people that have coached for Atlanta.
[ { "id": "A", "phrase": "Atlanta", "type": "finite", "ambiguity_type": "semantic_value", "interpretations": [ "Atlanta Hawks (tmID = 'ATL')", "Atlanta Crackers (tmID = 'ATC')" ], "intended_interpretation_idx": 1 } ]
[ { "id": "GQRY-A.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "COUNT(DISTINCT coachID)": 12 } ], "...
GQRY-A.1
007-0
ambig
true
retails
Count total number of distinct parts shipped in Q4 1996 and 1997 from orders with high order priority.
[ { "id": "A", "phrase": "Count total number of distinct parts shipped in Q4 1996 and 1997", "type": "finite", "ambiguity_type": "syntactic_computation", "interpretations": [ "count all distinct part in the specified period", "count total parts in Q4 1996 and count total parts in Q4 19...
[ { "id": "GQRY-A.0-B.0-C.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "total_distinct_parts": 120499 } ], ...
GQRY-A.0-B.1-C.0
048-0
ambig
true
github_repos
Count the number of repository IDs in YEAR_2023 that have public events and also received a large number of pull requests.
[ { "id": "A", "phrase": "public events", "type": "finite", "ambiguity_type": "semantic_computation", "interpretations": [ "events with attribute public=1", "events of type 'PublicEvent'" ], "intended_interpretation_idx": 1 }, { "id": "B", "phrase": "received a larg...
[ { "id": "GQRY-A.0-B.0", "query": null, "parameter_names": [ "pr_count_threshold" ], "parameter_values": { "pr_count_threshold": 12 }, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { ...
GQRY-A.1-B.1
053-0
ambig
true
github_repos
List the names of all repositories that contain large Python files or Java files.
[ { "id": "A", "phrase": "large", "type": "infinite", "ambiguity_type": "semantic_value", "parameter_name": "file_byte_threshold", "parameter_dtype": "int", "parameter_sample_operators": [ ">", ">=" ], "parameter_sample_values": [ 10240 ], "intended_parame...
[ { "id": "GQRY-B.0", "query": null, "parameter_names": [ "file_byte_threshold" ], "parameter_values": { "file_byte_threshold": 10240 }, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { ...
GQRY-B.0
016-2
ambig
true
retails
Show the number of suppliers and customers from America.
[ { "id": "A", "phrase": "suppliers and customers from America", "type": "finite", "ambiguity_type": "syntactic_computation", "interpretations": [ "suppliers AND (customers from America)", "(suppliers from America) AND (customers from America)" ], "intended_interpretation_idx":...
[ { "id": "GQRY-A.0-B.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "supplier_count": 10000, "customer_count": 6100 ...
GQRY-A.1-B.1
052-1
ambig
true
github_repos
List all repositories in YEAR_2023, and for each, return its name and the source (identified by name) that contribute most events to it.
[ { "id": "A", "phrase": "source", "type": "finite", "ambiguity_type": "semantic_column", "interpretations": [ "user", "organization" ], "intended_interpretation_idx": 0 } ]
[ { "id": "GQRY-A.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "repo_name": "0xSpaceShard/starknet-devnet", "source":...
GQRY-A.0
055-2
ambig
true
github_repos
Find emails of all contributors in the sample commits.
[ { "id": "A", "phrase": "contributors", "type": "finite", "ambiguity_type": "semantic_column", "interpretations": [ "commit author", "committer", "both commit author and committer" ], "intended_interpretation_idx": 1 } ]
[ { "id": "GQRY-A.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "email": "4a57785b02e7b752fc2eb7d1c97db94302a41bf7@users.noreply.git...
GQRY-A.1
006-0
ambig
true
retails
Count number of suppliers with negative balance or located in Africa and do not supply Brand#32.
[ { "id": "A", "phrase": "with negative balance or located in Africa and do not supply Brand#32", "type": "finite", "ambiguity_type": "syntactic_computation", "interpretations": [ "suppliers (with negative balance) OR (located in Africa AND do not supply Brand#32)", "suppliers (with ne...
[ { "id": "GQRY-A.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "COUNT(DISTINCT s.s_suppkey)": 998 } ], ...
GQRY-A.1
093-1
ambig
true
student_club
Show the number of members for each region in the Morgan County .
[ { "id": "A", "phrase": "region", "type": "finite", "ambiguity_type": "semantic_column", "interpretations": [ "zip code", "city" ], "intended_interpretation_idx": 1 }, { "id": "B", "phrase": "Morgan County", "type": "finite", "ambiguity_type": "semantic_val...
[ { "id": "GQRY-A.0-B.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "zip_code": 25411, "member_count": 0 }...
GQRY-A.1-B.1
023-1
ambig
true
retails
For each supplier with ID from 1 to 100, determine the total amount owed to them.
[ { "id": "A", "phrase": "total amount owed", "type": "finite", "ambiguity_type": "semantic_computation", "interpretations": [ "balance in the supplier's account", "value of open line items", "value of line items in unfinished orders" ], "intended_interpretation_idx": 2 ...
[ { "id": "GQRY-A.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "s_suppkey": 1, "s_name": "Supplier#000000001", ...
GQRY-A.2
029-3
ambig
true
professional_basketball
What is Charles Smith's best true shooting percentage in a season in his career?
[ { "id": "A", "phrase": "Charles Smith", "type": "finite", "ambiguity_type": "semantic_value", "interpretations": [ "Charles Smith from University of Pittsburgh born on July 16, 1965", "Charles Smith from Georgetown University born on November 29, 1967", "Charles Smith from Marq...
[ { "id": "GQRY-A.0-B.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "year": 1989, "true_shooting_percentage": 0.588896...
GQRY-A.1-B.0
086-1
ambig
true
codebase_community
Which post received the most responses?
[ { "id": "A", "phrase": "responses", "type": "finite", "ambiguity_type": "semantic_column", "interpretations": [ "answers", "comments", "both answers and comments" ], "intended_interpretation_idx": 2 } ]
[ { "id": "GQRY-A.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "post_id": 726, "post_title": "Famous statistician quo...
GQRY-A.2
023-2
ambig
true
retails
For each supplier with ID from 1 to 100, determine the total amount owed to them.
[ { "id": "A", "phrase": "total amount owed", "type": "finite", "ambiguity_type": "semantic_computation", "interpretations": [ "balance in the supplier's account", "value of open line items", "value of line items in unfinished orders" ], "intended_interpretation_idx": 0 ...
[ { "id": "GQRY-A.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "s_suppkey": 1, "s_name": "Supplier#000000001", ...
GQRY-A.0
065-2
ambig
true
financial
List the districts with low unemployment in 1995 - 1996.
[ { "id": "A", "phrase": "low unemployment", "type": "infinite", "ambiguity_type": "semantic_value", "parameter_name": "unemployment_rate_threshold", "parameter_dtype": "float", "parameter_sample_operators": [ "<", "<=" ], "parameter_sample_values": [ 1.7000000000...
[ { "id": "GQRY-B.0", "query": null, "parameter_names": [ "unemployment_rate_threshold" ], "parameter_values": { "unemployment_rate_threshold": 1.7000000000000002 }, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_dat...
GQRY-B.1
035-2
ambig
true
professional_basketball
Count the number of people who played or coached in the NBA finals in the 1990s.
[ { "id": "A", "phrase": "played or coached in the NBA finals in the 1990s", "type": "finite", "ambiguity_type": "syntactic_computation", "interpretations": [ "(played in the 1990s) or (coached in the NBA finals in the 1990s)", "(played or coached) in the NBA finals in the 1990s." ...
[ { "id": "GQRY-A.0-B.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "COUNT(DISTINCT personID)": 1027 } ], ...
GQRY-A.0-B.0
035-3
ambig
true
professional_basketball
Count the number of people who played or coached in the NBA finals in the 1990s.
[ { "id": "A", "phrase": "played or coached in the NBA finals in the 1990s", "type": "finite", "ambiguity_type": "syntactic_computation", "interpretations": [ "(played in the 1990s) or (coached in the NBA finals in the 1990s)", "(played or coached) in the NBA finals in the 1990s." ...
[ { "id": "GQRY-A.0-B.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "COUNT(DISTINCT personID)": 1027 } ], ...
GQRY-A.0-B.1
075-2
ambig
true
codebase_community
List all users in Tokyo and show total views for each of them.
[ { "id": "A", "phrase": "total views", "type": "finite", "ambiguity_type": "semantic_computation", "interpretations": [ "total profile views", "total views for authored posts", "total views for authored or edited posts" ], "intended_interpretation_idx": 2 } ]
[ { "id": "GQRY-A.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "UserId": 83, "DisplayName": "c4il", "To...
GQRY-A.2
088-2
ambig
true
student_club
For each region, report the total club funding received by members.
[ { "id": "A", "phrase": "region", "type": "finite", "ambiguity_type": "semantic_column", "interpretations": [ "zip code", "city", "county", "state" ], "intended_interpretation_idx": 0 } ]
[ { "id": "GQRY-A.0", "query": "SELECT z.zip_code, COALESCE(SUM(i.amount), 0) AS total_income\nFROM zip_code z\nLEFT JOIN member m ON m.zip = z.zip_code\nLEFT JOIN income i ON i.link_to_member = m.member_id\nGROUP BY z.zip_code\nORDER BY z.zip_code;", "parameter_names": [], "parameter_values": {}, ...
GQRY-A.0
007-4
ambig
true
retails
Count total number of distinct parts shipped in Q4 1996 and 1997 from orders with high order priority.
[ { "id": "A", "phrase": "Count total number of distinct parts shipped in Q4 1996 and 1997", "type": "finite", "ambiguity_type": "syntactic_computation", "interpretations": [ "count all distinct part in the specified period", "count total parts in Q4 1996 and count total parts in Q4 19...
[ { "id": "GQRY-A.0-B.0-C.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "total_distinct_parts": 120499 } ], ...
GQRY-A.1-B.0-C.0
020-2
ambig
true
retails
List large parts that haven't been shipped to Middle East countries. Only includes parts with ID <= 1000.
[ { "id": "A", "phrase": "large parts", "type": "finite", "ambiguity_type": "semantic_column", "interpretations": [ "p_size is high", "p_type starts with 'LARGE'" ], "intended_interpretation_idx": 0 }, { "id": "B", "phrase": "large parts", "type": "infinite", ...
[ { "id": "GQRY-A.0-C.0", "query": null, "parameter_names": [ "size_threshold" ], "parameter_values": { "size_threshold": 25 }, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "p_p...
GQRY-A.0-C.1
075-0
ambig
true
codebase_community
List all users in Tokyo and show total views for each of them.
[ { "id": "A", "phrase": "total views", "type": "finite", "ambiguity_type": "semantic_computation", "interpretations": [ "total profile views", "total views for authored posts", "total views for authored or edited posts" ], "intended_interpretation_idx": 0 } ]
[ { "id": "GQRY-A.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "UserId": 83, "DisplayName": "c4il", "To...
GQRY-A.0
010-1
ambig
true
retails
Find the regions associated with the highest-value order in the car industry.
[ { "id": "A", "phrase": "regions", "type": "finite", "ambiguity_type": "semantic_computation", "interpretations": [ "customer regions", "supplier regions" ], "intended_interpretation_idx": 1 } ]
[ { "id": "GQRY-A.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "r_regionkey": 3, "r_name": "EUROPE" } ...
GQRY-A.1
060-3
ambig
true
financial
Count the number of young clients with significant loans and large transactions for each area.
[ { "id": "A", "phrase": "Count the number of young clients with significant loans and large transactions", "type": "finite", "ambiguity_type": "semantic_computation", "interpretations": [ "count clients with either significant loans or large transactions ('and' means UNION)", "count c...
[ { "id": "GQRY-A.0-E.0", "query": null, "parameter_names": [ "loan_amount_threshold", "birth_date_threshold", "transaction_amount_threshold", "birth_date_threshold" ], "parameter_values": { "loan_amount_threshold": 12000, "birth_date_threshold": "1960-01-01", ...
GQRY-A.0-E.0
081-1
ambig
true
codebase_community
Find users who have either Teacher or Student badges in 2011 and 2012. Only includes the users with ID up to 1000.
[ { "id": "A", "phrase": "in 2011 and 2012", "type": "finite", "ambiguity_type": "semantic_computation", "interpretations": [ "in both 2011 and 2012.", "in either 2011 or 2012." ], "intended_interpretation_idx": 0 } ]
[ { "id": "GQRY-A.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "UserId": 501, "DisplayName": "momeara" },...
GQRY-A.0
090-0
ambig
true
student_club
List all events attended by members in Albany, including their name and location.
[ { "id": "A", "phrase": "Albany", "type": "finite", "ambiguity_type": "semantic_computation", "interpretations": [ "Albany city, Vermont", "Albany city, New York", "Albany city, Georgia", "Albany city, Kentucky", "Albany city, Ohio", "Albany city, Indiana", ...
[ { "id": "GQRY-A.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [], "num_rows": 0 }, "parquet_base64": "UEFSMRUEFQAVAkwVABUAEgAAABUEFQAV...
GQRY-A.15
002-1
ambig
true
retails
Count the number of suppliers that offer both air and rail shipping in America.
[ { "id": "A", "phrase": "suppliers that offer both air and rail shipping in America", "type": "finite", "ambiguity_type": "syntactic_computation", "interpretations": [ "suppliers that offer air and rail shipping to customers in America", "suppliers in America that offer air and rail s...
[ { "id": "GQRY-A.0-B.0-C.0", "query": "WITH usa_suppliers_with_air AS (\nSELECT DISTINCT l.l_suppkey\nFROM lineitem l\nJOIN orders o ON l.l_orderkey = o.o_orderkey\nJOIN customer c ON o.o_custkey = c.c_custkey\nJOIN nation n ON c.c_nationkey = n.n_nationkey\nWHERE n.n_name = 'UNITED STATES'\nAND l.l_shipmode...
GQRY-A.1-B.0-C.1
065-1
ambig
true
financial
List the districts with low unemployment in 1995 - 1996.
[ { "id": "A", "phrase": "low unemployment", "type": "infinite", "ambiguity_type": "semantic_value", "parameter_name": "unemployment_rate_threshold", "parameter_dtype": "float", "parameter_sample_operators": [ "<", "<=" ], "parameter_sample_values": [ 1.7000000000...
[ { "id": "GQRY-B.0", "query": null, "parameter_names": [ "unemployment_rate_threshold" ], "parameter_values": { "unemployment_rate_threshold": 1.7000000000000002 }, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_dat...
GQRY-B.0
002-3
ambig
true
retails
Count the number of suppliers that offer both air and rail shipping in America.
[ { "id": "A", "phrase": "suppliers that offer both air and rail shipping in America", "type": "finite", "ambiguity_type": "syntactic_computation", "interpretations": [ "suppliers that offer air and rail shipping to customers in America", "suppliers in America that offer air and rail s...
[ { "id": "GQRY-A.0-B.0-C.0", "query": "WITH usa_suppliers_with_air AS (\nSELECT DISTINCT l.l_suppkey\nFROM lineitem l\nJOIN orders o ON l.l_orderkey = o.o_orderkey\nJOIN customer c ON o.o_custkey = c.c_custkey\nJOIN nation n ON c.c_nationkey = n.n_nationkey\nWHERE n.n_name = 'UNITED STATES'\nAND l.l_shipmode...
GQRY-A.1-B.0-C.0
051-2
ambig
true
github_repos
For each sample repo with many watchers, show the number of public events in the first month of 2023 and 2022, return the result in (repo_name, count) pairs.
[ { "id": "A", "phrase": "many watchers", "type": "infinite", "ambiguity_type": "semantic_value", "parameter_name": "watcher_threshold", "parameter_dtype": "int", "parameter_sample_operators": [ ">", ">=" ], "parameter_sample_values": [ 160 ], "intended_pa...
[ { "id": "GQRY-B.0-C.0", "query": null, "parameter_names": [ "watcher_threshold" ], "parameter_values": { "watcher_threshold": 160 }, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { ...
GQRY-B.0-C.1
093-2
ambig
true
student_club
Show the number of members for each region in the Morgan County .
[ { "id": "A", "phrase": "region", "type": "finite", "ambiguity_type": "semantic_column", "interpretations": [ "zip code", "city" ], "intended_interpretation_idx": 0 }, { "id": "B", "phrase": "Morgan County", "type": "finite", "ambiguity_type": "semantic_val...
[ { "id": "GQRY-A.0-B.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "zip_code": 25411, "member_count": 0 }...
GQRY-A.0-B.4
083-0
ambig
true
codebase_community
For each tag with many occurences (tags.Count), find the post with the highest score and its last update timestamp and reply count.
[ { "id": "A", "phrase": "many occurences", "type": "infinite", "ambiguity_type": "semantic_value", "parameter_name": "count_threshold", "parameter_dtype": "int", "parameter_sample_operators": [ ">", ">=" ], "parameter_sample_values": [ 500 ], "intended_pa...
[ { "id": "GQRY-B.0-C.0", "query": null, "parameter_names": [ "count_threshold" ], "parameter_values": { "count_threshold": 500 }, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "...
GQRY-B.0-C.1
063-0
ambig
true
financial
Identify clients who are considered young adults when they received a sizable loan. Return the client ID, loan amount, and loan date.
[ { "id": "A", "phrase": "young", "type": "infinite", "ambiguity_type": "semantic_value", "parameter_name": "age_upper_bound", "parameter_dtype": "int", "parameter_sample_operators": [ "<", "<=" ], "parameter_sample_values": [ 25 ], "intended_parameter_ope...
[ { "id": "GQRY", "query": null, "parameter_names": [ "age_lower_bound", "age_upper_bound", "loan_amount_threshold" ], "parameter_values": { "age_lower_bound": 18, "age_upper_bound": 25, "loan_amount_threshold": 10000 }, "exec_result": { "df": { ...
GQRY
038-1
ambig
true
github_repos
Show all programming languages and their total usage in GITHUB_REPOS_LANGUAGES.
[ { "id": "A", "phrase": "total usage", "type": "finite", "ambiguity_type": "semantic_computation", "interpretations": [ "total number of repositories", "total number of bytes" ], "intended_interpretation_idx": 1 } ]
[ { "id": "GQRY-A.0", "query": null, "parameter_names": [], "parameter_values": {}, "exec_result": { "df": { "format": "parquet_base64_v1", "preview": { "sample_data": [ { "language": "Shell", "repo_count": 23 }, ...
GQRY-A.1