1sf/bird-sql-train-with-schema huggingface dataset:
Database: law_episode
Tables: Episode, Keyword, Person, Award, Credit, Vote
Columns (table index, column name): -1, *, 0, episode_id, 0, series, 0, season, 0, episode, 0, number_in_series, 0, title, 0, summary, 0, air_date, 0, episode_image, 0, rating, 0, votes, 1, episode_id, 1, keyword, 2, person_id, 2, name, 2, birthdate, 2, birth_name, 2, birth_place, 2, birth_region, 2, birth_country, 2, height_meters, 2, nickname, 3, award_id, 3, organization, 3, year, 3, award_category, 3, award, 3, series, 3, episode_id, 3, person_id, 3, role, 3, result, 4, episode_id, 4, person_id, 4, category, 4, role, 4, credited, 5, episode_id, 5, stars, 5, votes, 5, percent
Question: Which continent was Michael Preston born on?
Evidence: continent refers to birth_country
SQL: SELECT birth_country FROM Person WHERE name = 'Michael Preston'
Database: law_episode
Tables: Episode, Keyword, Person, Award, Credit, Vote
Columns (table index, column name): -1, *, 0, episode_id, 0, series, 0, season, 0, episode, 0, number_in_series, 0, title, 0, summary, 0, air_date, 0, episode_image, 0, rating, 0, votes, 1, episode_id, 1, keyword, 2, person_id, 2, name, 2, birthdate, 2, birth_name, 2, birth_place, 2, birth_region, 2, birth_country, 2, height_meters, 2, nickname, 3, award_id, 3, organization, 3, year, 3, award_category, 3, award, 3, series, 3, episode_id, 3, person_id, 3, role, 3, result, 4, episode_id, 4, person_id, 4, category, 4, role, 4, credited, 5, episode_id, 5, stars, 5, votes, 5, percent
Question: Who was the nominee playing the role of Katrina Ludlow in the Law & Order series?
Evidence: nominee refers to result = 'Nominee'; the role of Katrina Ludlow refers to role = 'Katrina Ludlow'
SQL: SELECT T2.name FROM Award AS T1 INNER JOIN Person AS T2 ON T1.person_id = T2.person_id WHERE T1.result = 'Nominee' AND T1.role = 'Katrina Ludlow' AND T1.series = 'Law and Order'
Database: law_episode
Tables: Episode, Keyword, Person, Award, Credit, Vote
Columns (table index, column name): -1, *, 0, episode_id, 0, series, 0, season, 0, episode, 0, number_in_series, 0, title, 0, summary, 0, air_date, 0, episode_image, 0, rating, 0, votes, 1, episode_id, 1, keyword, 2, person_id, 2, name, 2, birthdate, 2, birth_name, 2, birth_place, 2, birth_region, 2, birth_country, 2, height_meters, 2, nickname, 3, award_id, 3, organization, 3, year, 3, award_category, 3, award, 3, series, 3, episode_id, 3, person_id, 3, role, 3, result, 4, episode_id, 4, person_id, 4, category, 4, role, 4, credited, 5, episode_id, 5, stars, 5, votes, 5, percent
Question: Who played the role of a teleplay in the episode that won "Best Television Episode"?
Evidence: the role of a teleplay refers to role = 'teleplay'; won refers to result = 'Winner'; "Best Television Episode" refers to award = 'Best Television Episode'
SQL: SELECT T2.name FROM Award AS T1 INNER JOIN Person AS T2 ON T1.person_id = T2.person_id WHERE T1.result = 'Winner' AND T1.award = 'Best Television Episode'
Database: law_episode
Tables: Episode, Keyword, Person, Award, Credit, Vote
Columns (table index, column name): -1, *, 0, episode_id, 0, series, 0, season, 0, episode, 0, number_in_series, 0, title, 0, summary, 0, air_date, 0, episode_image, 0, rating, 0, votes, 1, episode_id, 1, keyword, 2, person_id, 2, name, 2, birthdate, 2, birth_name, 2, birth_place, 2, birth_region, 2, birth_country, 2, height_meters, 2, nickname, 3, award_id, 3, organization, 3, year, 3, award_category, 3, award, 3, series, 3, episode_id, 3, person_id, 3, role, 3, result, 4, episode_id, 4, person_id, 4, category, 4, role, 4, credited, 5, episode_id, 5, stars, 5, votes, 5, percent
Question: What is the date of birth of the actor who played the role of a "writer"?
Evidence: date of birth refers to birthdate
SQL: SELECT T2.birthdate FROM Award AS T1 INNER JOIN Person AS T2 ON T1.person_id = T2.person_id WHERE T1.role = 'writer'
Database: law_episode
Tables: Episode, Keyword, Person, Award, Credit, Vote
Columns (table index, column name): -1, *, 0, episode_id, 0, series, 0, season, 0, episode, 0, number_in_series, 0, title, 0, summary, 0, air_date, 0, episode_image, 0, rating, 0, votes, 1, episode_id, 1, keyword, 2, person_id, 2, name, 2, birthdate, 2, birth_name, 2, birth_place, 2, birth_region, 2, birth_country, 2, height_meters, 2, nickname, 3, award_id, 3, organization, 3, year, 3, award_category, 3, award, 3, series, 3, episode_id, 3, person_id, 3, role, 3, result, 4, episode_id, 4, person_id, 4, category, 4, role, 4, credited, 5, episode_id, 5, stars, 5, votes, 5, percent
Question: Which episode was nominated for the award for "Outstanding Costume Design for a Series"?
Evidence: episode refers to title; "Outstanding Costume Design for a Series" refers to award = 'Outstanding Costume Design for a Series'
SQL: SELECT T2.title FROM Award AS T1 INNER JOIN Episode AS T2 ON T1.episode_id = T2.episode_id WHERE T1.award = 'Outstanding Costume Design for a Series'
Database: law_episode
Tables: Episode, Keyword, Person, Award, Credit, Vote
Columns (table index, column name): -1, *, 0, episode_id, 0, series, 0, season, 0, episode, 0, number_in_series, 0, title, 0, summary, 0, air_date, 0, episode_image, 0, rating, 0, votes, 1, episode_id, 1, keyword, 2, person_id, 2, name, 2, birthdate, 2, birth_name, 2, birth_place, 2, birth_region, 2, birth_country, 2, height_meters, 2, nickname, 3, award_id, 3, organization, 3, year, 3, award_category, 3, award, 3, series, 3, episode_id, 3, person_id, 3, role, 3, result, 4, episode_id, 4, person_id, 4, category, 4, role, 4, credited, 5, episode_id, 5, stars, 5, votes, 5, percent
Question: Which episode has the highest total number of viewer votes?
Evidence: episode refers to title; the highest total number of viewer votes refers to max(sum(votes))
SQL: SELECT T1.title FROM Episode AS T1 INNER JOIN Vote AS T2 ON T1.episode_id = T2.episode_id GROUP BY T1.title ORDER BY SUM(T1.votes) DESC LIMIT 1
Database: law_episode
Tables: Episode, Keyword, Person, Award, Credit, Vote
Columns (table index, column name): -1, *, 0, episode_id, 0, series, 0, season, 0, episode, 0, number_in_series, 0, title, 0, summary, 0, air_date, 0, episode_image, 0, rating, 0, votes, 1, episode_id, 1, keyword, 2, person_id, 2, name, 2, birthdate, 2, birth_name, 2, birth_place, 2, birth_region, 2, birth_country, 2, height_meters, 2, nickname, 3, award_id, 3, organization, 3, year, 3, award_category, 3, award, 3, series, 3, episode_id, 3, person_id, 3, role, 3, result, 4, episode_id, 4, person_id, 4, category, 4, role, 4, credited, 5, episode_id, 5, stars, 5, votes, 5, percent
Question: Who was the actor who was portraying "Alex Brown" and has been credited?
Evidence: who refers to name; portraying "Alex Brown" refers to role = 'Alex Brown'; has been credited refers to credited = 'true'
SQL: SELECT T1.name FROM Person AS T1 INNER JOIN Credit AS T2 ON T1.person_id = T2.person_id WHERE T2.role = 'Alex Brown' AND T2.credited = 'true'
Database: law_episode
Tables: Episode, Keyword, Person, Award, Credit, Vote
Columns (table index, column name): -1, *, 0, episode_id, 0, series, 0, season, 0, episode, 0, number_in_series, 0, title, 0, summary, 0, air_date, 0, episode_image, 0, rating, 0, votes, 1, episode_id, 1, keyword, 2, person_id, 2, name, 2, birthdate, 2, birth_name, 2, birth_place, 2, birth_region, 2, birth_country, 2, height_meters, 2, nickname, 3, award_id, 3, organization, 3, year, 3, award_category, 3, award, 3, series, 3, episode_id, 3, person_id, 3, role, 3, result, 4, episode_id, 4, person_id, 4, category, 4, role, 4, credited, 5, episode_id, 5, stars, 5, votes, 5, percent
Question: Where is the place of birth of the actor with the number nm0007064 who has not been credited for playing the role of a "Narrator"?
Evidence: place of birth refers to birth_place; actor with the number nm0007064 refers to person_id = 'nm007064'; has not been credited refers to credited = ''; the role of a "Narrator" refers to role = 'narrator'
SQL: SELECT DISTINCT T1.birth_place FROM Person AS T1 INNER JOIN Credit AS T2 ON T1.person_id = T2.person_id WHERE T1.person_id = 'nm0007064' AND T2.role = 'Narrator' AND T2.credited = 'false'
Database: law_episode
Tables: Episode, Keyword, Person, Award, Credit, Vote
Columns (table index, column name): -1, *, 0, episode_id, 0, series, 0, season, 0, episode, 0, number_in_series, 0, title, 0, summary, 0, air_date, 0, episode_image, 0, rating, 0, votes, 1, episode_id, 1, keyword, 2, person_id, 2, name, 2, birthdate, 2, birth_name, 2, birth_place, 2, birth_region, 2, birth_country, 2, height_meters, 2, nickname, 3, award_id, 3, organization, 3, year, 3, award_category, 3, award, 3, series, 3, episode_id, 3, person_id, 3, role, 3, result, 4, episode_id, 4, person_id, 4, category, 4, role, 4, credited, 5, episode_id, 5, stars, 5, votes, 5, percent
Question: What are the keywords of the episode "Shield"?
Evidence: the episode "Shield" refers to title = 'Shield'
SQL: SELECT T2.keyword FROM Episode AS T1 INNER JOIN Keyword AS T2 ON T1.episode_id = T2.episode_id WHERE T1.title = 'Shield'
Database: law_episode
Tables: Episode, Keyword, Person, Award, Credit, Vote
Columns (table index, column name): -1, *, 0, episode_id, 0, series, 0, season, 0, episode, 0, number_in_series, 0, title, 0, summary, 0, air_date, 0, episode_image, 0, rating, 0, votes, 1, episode_id, 1, keyword, 2, person_id, 2, name, 2, birthdate, 2, birth_name, 2, birth_place, 2, birth_region, 2, birth_country, 2, height_meters, 2, nickname, 3, award_id, 3, organization, 3, year, 3, award_category, 3, award, 3, series, 3, episode_id, 3, person_id, 3, role, 3, result, 4, episode_id, 4, person_id, 4, category, 4, role, 4, credited, 5, episode_id, 5, stars, 5, votes, 5, percent
Question: Who are the actors with a height of over 1.80m in an episode that won an award?
Evidence: who refers to name; a height of over 1.80m refers to height_meters > 1.80; won an award refers to result = 'Winner'
SQL: SELECT T2.name FROM Award AS T1 INNER JOIN Person AS T2 ON T1.person_id = T2.person_id WHERE T1.result = 'Winner' AND T2.height_meters > 1.80
Database: law_episode
Tables: Episode, Keyword, Person, Award, Credit, Vote
Columns (table index, column name): -1, *, 0, episode_id, 0, series, 0, season, 0, episode, 0, number_in_series, 0, title, 0, summary, 0, air_date, 0, episode_image, 0, rating, 0, votes, 1, episode_id, 1, keyword, 2, person_id, 2, name, 2, birthdate, 2, birth_name, 2, birth_place, 2, birth_region, 2, birth_country, 2, height_meters, 2, nickname, 3, award_id, 3, organization, 3, year, 3, award_category, 3, award, 3, series, 3, episode_id, 3, person_id, 3, role, 3, result, 4, episode_id, 4, person_id, 4, category, 4, role, 4, credited, 5, episode_id, 5, stars, 5, votes, 5, percent
Question: Which episode has the two keywords "nun" and "priest"?
Evidence: episode refers to title; the two keywords "nun" and "priest" refers to keyword = 'nun' or keyword = 'priest';
SQL: SELECT T1.title FROM Episode AS T1 INNER JOIN Keyword AS T2 ON T1.episode_id = T2.episode_id WHERE T2.keyword IN ('nun', 'priest')
Database: law_episode
Tables: Episode, Keyword, Person, Award, Credit, Vote
Columns (table index, column name): -1, *, 0, episode_id, 0, series, 0, season, 0, episode, 0, number_in_series, 0, title, 0, summary, 0, air_date, 0, episode_image, 0, rating, 0, votes, 1, episode_id, 1, keyword, 2, person_id, 2, name, 2, birthdate, 2, birth_name, 2, birth_place, 2, birth_region, 2, birth_country, 2, height_meters, 2, nickname, 3, award_id, 3, organization, 3, year, 3, award_category, 3, award, 3, series, 3, episode_id, 3, person_id, 3, role, 3, result, 4, episode_id, 4, person_id, 4, category, 4, role, 4, credited, 5, episode_id, 5, stars, 5, votes, 5, percent
Question: Which episode number has the second highest positive viewer comments and has been awarded "Best Television Episode"?
Evidence: episode number refers to episode_id; awarded "Best Television Episode" refers to award = 'Best Television Episode' and result = 'Winner'; the second highest positive viewer comments refers to rating = 8.5
SQL: SELECT T2.episode_id FROM Award AS T1 INNER JOIN Episode AS T2 ON T1.episode_id = T2.episode_id WHERE T1.award = 'Best Television Episode' AND T1.result = 'Winner' ORDER BY T2.rating DESC LIMIT 2
Database: law_episode
Tables: Episode, Keyword, Person, Award, Credit, Vote
Columns (table index, column name): -1, *, 0, episode_id, 0, series, 0, season, 0, episode, 0, number_in_series, 0, title, 0, summary, 0, air_date, 0, episode_image, 0, rating, 0, votes, 1, episode_id, 1, keyword, 2, person_id, 2, name, 2, birthdate, 2, birth_name, 2, birth_place, 2, birth_region, 2, birth_country, 2, height_meters, 2, nickname, 3, award_id, 3, organization, 3, year, 3, award_category, 3, award, 3, series, 3, episode_id, 3, person_id, 3, role, 3, result, 4, episode_id, 4, person_id, 4, category, 4, role, 4, credited, 5, episode_id, 5, stars, 5, votes, 5, percent
Question: Please list any three episodes that were most enjoyed by the viewers.
Evidence: episode refers to title; most enjoyed by the viewers refers to stars = 10
SQL: SELECT T1.title FROM Episode AS T1 INNER JOIN Vote AS T2 ON T1.episode_id = T2.episode_id WHERE T2.stars = 10 LIMIT 3
Database: synthea
Tables: all_prevalences, patients, encounters, allergies, careplans, conditions, immunizations, medications, observations, procedures, claims
Columns (table index, column name): -1, *, 0, ITEM, 0, POPULATION TYPE, 0, OCCURRENCES, 0, POPULATION COUNT, 0, PREVALENCE RATE, 0, PREVALENCE PERCENTAGE, 1, patient, 1, birthdate, 1, deathdate, 1, ssn, 1, drivers, 1, passport, 1, prefix, 1, first, 1, last, 1, suffix, 1, maiden, 1, marital, 1, race, 1, ethnicity, 1, gender, 1, birthplace, 1, address, 2, ID, 2, DATE, 2, PATIENT, 2, CODE, 2, DESCRIPTION, 2, REASONCODE, 2, REASONDESCRIPTION, 3, START, 3, STOP, 3, PATIENT, 3, ENCOUNTER, 3, CODE, 3, DESCRIPTION, 4, ID, 4, START, 4, STOP, 4, PATIENT, 4, ENCOUNTER, 4, CODE, 4, DESCRIPTION, 4, REASONCODE, 4, REASONDESCRIPTION, 5, START, 5, STOP, 5, PATIENT, 5, ENCOUNTER, 5, CODE, 5, DESCRIPTION, 6, DATE, 6, PATIENT, 6, ENCOUNTER, 6, CODE, 6, DESCRIPTION, 7, START, 7, STOP, 7, PATIENT, 7, ENCOUNTER, 7, CODE, 7, DESCRIPTION, 7, REASONCODE, 7, REASONDESCRIPTION, 8, DATE, 8, PATIENT, 8, ENCOUNTER, 8, CODE, 8, DESCRIPTION, 8, VALUE, 8, UNITS, 9, DATE, 9, PATIENT, 9, ENCOUNTER, 9, CODE, 9, DESCRIPTION, 9, REASONCODE, 9, REASONDESCRIPTION, 10, ID, 10, PATIENT, 10, BILLABLEPERIOD, 10, ORGANIZATION, 10, ENCOUNTER, 10, DIAGNOSIS, 10, TOTAL
Question: According to the observation on 2008/3/11, what was the height of Elly Koss?
Evidence: 2008/3/11 refers to date = '2008-03-11'; height refers to DESCRIPTION = 'Body Height' from observations;
SQL: SELECT T2.value, T2.units FROM patients AS T1 INNER JOIN observations AS T2 ON T1.patient = T2.PATIENT WHERE T1.first = 'Elly' AND T1.last = 'Koss' AND T2.date = '2008-03-11' AND T2.description = 'Body Height'
Database: synthea
Tables: all_prevalences, patients, encounters, allergies, careplans, conditions, immunizations, medications, observations, procedures, claims
Columns (table index, column name): -1, *, 0, ITEM, 0, POPULATION TYPE, 0, OCCURRENCES, 0, POPULATION COUNT, 0, PREVALENCE RATE, 0, PREVALENCE PERCENTAGE, 1, patient, 1, birthdate, 1, deathdate, 1, ssn, 1, drivers, 1, passport, 1, prefix, 1, first, 1, last, 1, suffix, 1, maiden, 1, marital, 1, race, 1, ethnicity, 1, gender, 1, birthplace, 1, address, 2, ID, 2, DATE, 2, PATIENT, 2, CODE, 2, DESCRIPTION, 2, REASONCODE, 2, REASONDESCRIPTION, 3, START, 3, STOP, 3, PATIENT, 3, ENCOUNTER, 3, CODE, 3, DESCRIPTION, 4, ID, 4, START, 4, STOP, 4, PATIENT, 4, ENCOUNTER, 4, CODE, 4, DESCRIPTION, 4, REASONCODE, 4, REASONDESCRIPTION, 5, START, 5, STOP, 5, PATIENT, 5, ENCOUNTER, 5, CODE, 5, DESCRIPTION, 6, DATE, 6, PATIENT, 6, ENCOUNTER, 6, CODE, 6, DESCRIPTION, 7, START, 7, STOP, 7, PATIENT, 7, ENCOUNTER, 7, CODE, 7, DESCRIPTION, 7, REASONCODE, 7, REASONDESCRIPTION, 8, DATE, 8, PATIENT, 8, ENCOUNTER, 8, CODE, 8, DESCRIPTION, 8, VALUE, 8, UNITS, 9, DATE, 9, PATIENT, 9, ENCOUNTER, 9, CODE, 9, DESCRIPTION, 9, REASONCODE, 9, REASONDESCRIPTION, 10, ID, 10, PATIENT, 10, BILLABLEPERIOD, 10, ORGANIZATION, 10, ENCOUNTER, 10, DIAGNOSIS, 10, TOTAL
Question: By how much did Elly Koss's weight increase from the observation in 2008 to the observation in 2009?
Evidence: SUBTRACT((DATE like '2009%'), (DATE like '2008%')) where DESCRIPTION = 'Body Weight';
SQL: SELECT SUM(CASE WHEN strftime('%Y', T2.date) = '2009' THEN T2.VALUE END) - SUM(CASE WHEN strftime('%Y', T2.date) = '2008' THEN T2.VALUE END) AS increase , T2.units FROM patients AS T1 INNER JOIN observations AS T2 ON T1.patient = T2.PATIENT WHERE T1.first = 'Elly' AND T1.last = 'Koss' AND T2.description = 'Body Height'
Database: synthea
Tables: all_prevalences, patients, encounters, allergies, careplans, conditions, immunizations, medications, observations, procedures, claims
Columns (table index, column name): -1, *, 0, ITEM, 0, POPULATION TYPE, 0, OCCURRENCES, 0, POPULATION COUNT, 0, PREVALENCE RATE, 0, PREVALENCE PERCENTAGE, 1, patient, 1, birthdate, 1, deathdate, 1, ssn, 1, drivers, 1, passport, 1, prefix, 1, first, 1, last, 1, suffix, 1, maiden, 1, marital, 1, race, 1, ethnicity, 1, gender, 1, birthplace, 1, address, 2, ID, 2, DATE, 2, PATIENT, 2, CODE, 2, DESCRIPTION, 2, REASONCODE, 2, REASONDESCRIPTION, 3, START, 3, STOP, 3, PATIENT, 3, ENCOUNTER, 3, CODE, 3, DESCRIPTION, 4, ID, 4, START, 4, STOP, 4, PATIENT, 4, ENCOUNTER, 4, CODE, 4, DESCRIPTION, 4, REASONCODE, 4, REASONDESCRIPTION, 5, START, 5, STOP, 5, PATIENT, 5, ENCOUNTER, 5, CODE, 5, DESCRIPTION, 6, DATE, 6, PATIENT, 6, ENCOUNTER, 6, CODE, 6, DESCRIPTION, 7, START, 7, STOP, 7, PATIENT, 7, ENCOUNTER, 7, CODE, 7, DESCRIPTION, 7, REASONCODE, 7, REASONDESCRIPTION, 8, DATE, 8, PATIENT, 8, ENCOUNTER, 8, CODE, 8, DESCRIPTION, 8, VALUE, 8, UNITS, 9, DATE, 9, PATIENT, 9, ENCOUNTER, 9, CODE, 9, DESCRIPTION, 9, REASONCODE, 9, REASONDESCRIPTION, 10, ID, 10, PATIENT, 10, BILLABLEPERIOD, 10, ORGANIZATION, 10, ENCOUNTER, 10, DIAGNOSIS, 10, TOTAL
Question: During all the observations of Elly Koss, what was the highest Systolic Blood Pressure observed?
Evidence: the highest Systolic Blood Pressure refers to MAX(DESCRIPTION = 'Systolic Blood Pressure') from observations;
SQL: SELECT T2.value, T2.units FROM patients AS T1 INNER JOIN observations AS T2 ON T1.patient = T2.PATIENT WHERE T1.first = 'Elly' AND T1.last = 'Koss' AND T2.description = 'Systolic Blood Pressure' ORDER BY T2.VALUE DESC LIMIT 1
Database: synthea
Tables: all_prevalences, patients, encounters, allergies, careplans, conditions, immunizations, medications, observations, procedures, claims
Columns (table index, column name): -1, *, 0, ITEM, 0, POPULATION TYPE, 0, OCCURRENCES, 0, POPULATION COUNT, 0, PREVALENCE RATE, 0, PREVALENCE PERCENTAGE, 1, patient, 1, birthdate, 1, deathdate, 1, ssn, 1, drivers, 1, passport, 1, prefix, 1, first, 1, last, 1, suffix, 1, maiden, 1, marital, 1, race, 1, ethnicity, 1, gender, 1, birthplace, 1, address, 2, ID, 2, DATE, 2, PATIENT, 2, CODE, 2, DESCRIPTION, 2, REASONCODE, 2, REASONDESCRIPTION, 3, START, 3, STOP, 3, PATIENT, 3, ENCOUNTER, 3, CODE, 3, DESCRIPTION, 4, ID, 4, START, 4, STOP, 4, PATIENT, 4, ENCOUNTER, 4, CODE, 4, DESCRIPTION, 4, REASONCODE, 4, REASONDESCRIPTION, 5, START, 5, STOP, 5, PATIENT, 5, ENCOUNTER, 5, CODE, 5, DESCRIPTION, 6, DATE, 6, PATIENT, 6, ENCOUNTER, 6, CODE, 6, DESCRIPTION, 7, START, 7, STOP, 7, PATIENT, 7, ENCOUNTER, 7, CODE, 7, DESCRIPTION, 7, REASONCODE, 7, REASONDESCRIPTION, 8, DATE, 8, PATIENT, 8, ENCOUNTER, 8, CODE, 8, DESCRIPTION, 8, VALUE, 8, UNITS, 9, DATE, 9, PATIENT, 9, ENCOUNTER, 9, CODE, 9, DESCRIPTION, 9, REASONCODE, 9, REASONDESCRIPTION, 10, ID, 10, PATIENT, 10, BILLABLEPERIOD, 10, ORGANIZATION, 10, ENCOUNTER, 10, DIAGNOSIS, 10, TOTAL
Question: For how many times had Elly Koss have her Systolic Blood Pressure observed?
Evidence: Systolic Blood Pressure refers to DESCRIPTION = 'Systolic Blood Pressure';
SQL: SELECT COUNT(T2.description) FROM patients AS T1 INNER JOIN observations AS T2 ON T1.patient = T2.PATIENT WHERE T1.first = 'Elly' AND T1.last = 'Koss' AND T2.description = 'Systolic Blood Pressure'
Database: synthea
Tables: all_prevalences, patients, encounters, allergies, careplans, conditions, immunizations, medications, observations, procedures, claims
Columns (table index, column name): -1, *, 0, ITEM, 0, POPULATION TYPE, 0, OCCURRENCES, 0, POPULATION COUNT, 0, PREVALENCE RATE, 0, PREVALENCE PERCENTAGE, 1, patient, 1, birthdate, 1, deathdate, 1, ssn, 1, drivers, 1, passport, 1, prefix, 1, first, 1, last, 1, suffix, 1, maiden, 1, marital, 1, race, 1, ethnicity, 1, gender, 1, birthplace, 1, address, 2, ID, 2, DATE, 2, PATIENT, 2, CODE, 2, DESCRIPTION, 2, REASONCODE, 2, REASONDESCRIPTION, 3, START, 3, STOP, 3, PATIENT, 3, ENCOUNTER, 3, CODE, 3, DESCRIPTION, 4, ID, 4, START, 4, STOP, 4, PATIENT, 4, ENCOUNTER, 4, CODE, 4, DESCRIPTION, 4, REASONCODE, 4, REASONDESCRIPTION, 5, START, 5, STOP, 5, PATIENT, 5, ENCOUNTER, 5, CODE, 5, DESCRIPTION, 6, DATE, 6, PATIENT, 6, ENCOUNTER, 6, CODE, 6, DESCRIPTION, 7, START, 7, STOP, 7, PATIENT, 7, ENCOUNTER, 7, CODE, 7, DESCRIPTION, 7, REASONCODE, 7, REASONDESCRIPTION, 8, DATE, 8, PATIENT, 8, ENCOUNTER, 8, CODE, 8, DESCRIPTION, 8, VALUE, 8, UNITS, 9, DATE, 9, PATIENT, 9, ENCOUNTER, 9, CODE, 9, DESCRIPTION, 9, REASONCODE, 9, REASONDESCRIPTION, 10, ID, 10, PATIENT, 10, BILLABLEPERIOD, 10, ORGANIZATION, 10, ENCOUNTER, 10, DIAGNOSIS, 10, TOTAL
Question: The highest Systolic Blood Pressure was observed in which patient? Please give his or her full name.
Evidence: the highest Systolic Blood Pressure refers to MAX(DESCRIPTION = 'Systolic Blood Pressure') from observations; full name refers to first, last;
SQL: SELECT T1.first, T1.last FROM patients AS T1 INNER JOIN observations AS T2 ON T1.patient = T2.PATIENT WHERE T2.VALUE = ( SELECT MAX(VALUE) FROM observations WHERE description = 'Systolic Blood Pressure' ) LIMIT 1
Database: synthea
Tables: all_prevalences, patients, encounters, allergies, careplans, conditions, immunizations, medications, observations, procedures, claims
Columns (table index, column name): -1, *, 0, ITEM, 0, POPULATION TYPE, 0, OCCURRENCES, 0, POPULATION COUNT, 0, PREVALENCE RATE, 0, PREVALENCE PERCENTAGE, 1, patient, 1, birthdate, 1, deathdate, 1, ssn, 1, drivers, 1, passport, 1, prefix, 1, first, 1, last, 1, suffix, 1, maiden, 1, marital, 1, race, 1, ethnicity, 1, gender, 1, birthplace, 1, address, 2, ID, 2, DATE, 2, PATIENT, 2, CODE, 2, DESCRIPTION, 2, REASONCODE, 2, REASONDESCRIPTION, 3, START, 3, STOP, 3, PATIENT, 3, ENCOUNTER, 3, CODE, 3, DESCRIPTION, 4, ID, 4, START, 4, STOP, 4, PATIENT, 4, ENCOUNTER, 4, CODE, 4, DESCRIPTION, 4, REASONCODE, 4, REASONDESCRIPTION, 5, START, 5, STOP, 5, PATIENT, 5, ENCOUNTER, 5, CODE, 5, DESCRIPTION, 6, DATE, 6, PATIENT, 6, ENCOUNTER, 6, CODE, 6, DESCRIPTION, 7, START, 7, STOP, 7, PATIENT, 7, ENCOUNTER, 7, CODE, 7, DESCRIPTION, 7, REASONCODE, 7, REASONDESCRIPTION, 8, DATE, 8, PATIENT, 8, ENCOUNTER, 8, CODE, 8, DESCRIPTION, 8, VALUE, 8, UNITS, 9, DATE, 9, PATIENT, 9, ENCOUNTER, 9, CODE, 9, DESCRIPTION, 9, REASONCODE, 9, REASONDESCRIPTION, 10, ID, 10, PATIENT, 10, BILLABLEPERIOD, 10, ORGANIZATION, 10, ENCOUNTER, 10, DIAGNOSIS, 10, TOTAL
Question: For how long was Elly Koss required to take Acetaminophen?
Evidence: SUM(MULTIPLY(365, SUBTRACT(strftime('%Y', STOP), strftime('%Y', START))), MULTIPLY(30, SUBTRACT(strftime('%m', STOP), strftime('%m', START))), SUBTRACT(strftime('%d', STOP), strftime('%d', START))) where DESCRIPTION like 'Acetaminophen%';
SQL: SELECT strftime('%J', T2.STOP) - strftime('%J', T2.START) AS days FROM patients AS T1 INNER JOIN medications AS T2 ON T1.patient = T2.PATIENT WHERE T1.first = 'Elly' AND T1.last = 'Koss' AND T2.description LIKE 'Acetaminophen%'