System:
You are an expert in writing database language. You can write a corresponding database language query to answer the user's question based on the table structure described by the table creation statement. ##Table Structure
CREATE TABLE transportation.vehicles ( vehicle_id.text, license_plate.text, vin.text, make.text, model.text, year.integer, type.text, capacity.integer, fuel_type.text, status.text, depot_id.text, acquisition_date.date )
CREATE TABLE transportation.routes ( route_id.text, route_number.text, description.text, origin_location_id.text, destination_location_id.text, distance_km.numeric, estimated_duration_minutes.integer, type.text )
CREATE TABLE transportation.trips ( trip_id.text, route_id.text, vehicle_id.text, driver_id.text, scheduled_departure.timestamp, actual_departure.timestamp, scheduled_arrival.timestamp, actual_arrival.timestamp, origin_location_id.text, destination_location_id.text, status.text, passenger_count.integer, cargo_manifest_id.text )
CREATE TABLE transportation.fuel_logs ( fuel_log_id.text, vehicle_id.text, trip_id.text, log_timestamp.timestamp, fuel_type.text, quantity.numeric, unit.text, cost_per_unit.numeric, total_cost.numeric, odometer_reading.integer, location_id.text )
CREATE TABLE transportation.passengers ( passenger_id.text, first_name.text, last_name.text, email.text, phone_number.text, date_of_birth.date, loyalty_program_id.text, created_at.timestamp )
##Table Structure
CREATE TABLE social_media.users ( user_id text, username text, email text, password_hash text, full_name text, profile_picture_url text, bio text, location text, created_at timestamp, updated_at timestamp, is_verified boolean )
CREATE TABLE social_media.posts ( post_id character varying(64) NOT NULL, user_id character varying(64) NOT NULL, content text, media_url text, media_type character varying(20), created_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, updated_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, visibility character varying(20) NOT NULL DEFAULT 'public', location_lat numeric(9,6), location_lon numeric(9,6), PRIMARY KEY (post_id) )
CREATE TABLE social_media.post_hashtags (
    post_hashtag_id character varying(64) NOT NULL, -- unique identifier for the post-hashtag link
    post_id character varying(64) NOT NULL, -- identifier of the post (FK to posts.post_id)
    hashtag_id character varying(64) NOT NULL, -- identifier of the hashtag (FK to hashtags.hashtag_id)
    PRIMARY KEY (post_hashtag_id),
    CONSTRAINT unique_post_hashtag UNIQUE (post_id, hashtag_id) -- prevent duplicate tags on a post
)
CREATE TABLE social_media.messages ( message_id text PRIMARY KEY, conversation_id text, sender_user_id text, content text, media_url text, media_type text, sent_at timestamp, read_at timestamp )
CREATE TABLE social_media.conversation_participants ( participant_id text PRIMARY KEY, conversation_id text, user_id text, joined_at timestamp, last_read_at timestamp )
CREATE TABLE social_media.notifications ( notification_id.text, recipient_user_id.text, sender_user_id.text, notification_type.text, target_entity_id.text, target_entity_type.text, created_at.timestamp, read_at.timestamp )
CREATE TABLE social_media.user_settings ( setting_id text, user_id text, theme text, email_notifications_enabled boolean, push_notifications_enabled boolean, private_profile boolean, updated_at timestamp )
##Table Structure
CREATE TABLE legal_services.cases ( case_id.text, case_number.text, case_name.text, client_id.text, lead_lawyer_id.text, case_type.text, status.text, date_opened.timestamp, date_closed.timestamp, description.text, court_jurisdiction.text )
CREATE TABLE legal_services.time_entries (
    entry_id character varying(64) NOT NULL,  -- unique identifier for the time entry
    case_id character varying(64) NOT NULL, -- FK to cases table
    lawyer_id character varying(64) NOT NULL, -- FK to lawyers table (who performed the work)
    date_worked date NOT NULL, -- date the work was performed
    hours_spent numeric(5, 2) NOT NULL CHECK (hours_spent > 0), -- duration of work in hours (e.g., 1.5 for 1h 30m)
    billing_rate numeric(10, 2) NOT NULL, -- hourly rate applied for this entry
    description text NOT NULL, -- detailed description of the work performed
    is_billable boolean DEFAULT true, -- whether this time entry is billable to the client
    is_billed boolean DEFAULT false, -- whether this entry has been included in an invoice
    invoice_id character varying(64), -- FK to invoices table (once billed)
    created_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, -- when the entry was recorded
    PRIMARY KEY (entry_id)
)
CREATE TABLE legal_services.appointments (
    appointment_id character varying(64) NOT NULL, -- unique identifier for the appointment
    client_id character varying(64) NOT NULL, -- FK to clients table
    lawyer_id character varying(64) NOT NULL, -- FK to lawyers table
    case_id character varying(64), -- FK to cases table (optional, if related to a specific case)
    start_time timestamp NOT NULL, -- scheduled start date and time
    end_time timestamp NOT NULL, -- scheduled end date and time
    location text, -- location of the meeting (address or virtual link)
    subject character varying(255), -- subject or purpose of the appointment
    notes text, -- additional notes for the appointment
    status character varying(50) NOT NULL, -- e.g., Scheduled, Completed, Canceled, Rescheduled
    created_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP,
    PRIMARY KEY (appointment_id)
)
##Table Structure
CREATE TABLE hospitality_technology.payments ( payment_id text, reservation_id text, guest_id text, bill_id text, amount numeric, currency_code text, payment_method text, card_type text, card_last_four text, transaction_ref text, payment_timestamp timestamp, status text, staff_id_processed text, notes text )
##Table Structure
CREATE TABLE insurance.claims ( claim_id text PRIMARY KEY, policy_id text, customer_id text, incident_date timestamp, reported_date timestamp, description text, estimated_loss numeric, status text, settlement_amount numeric, settlement_date date, claim_handler_id text, police_report_number text )
CREATE TABLE insurance.insurance_products ( product_id text PRIMARY KEY, product_name text, product_type text, description text, base_premium numeric, coverage_details text, underwriting_rules text, is_active boolean, created_at timestamp, updated_at timestamp )
CREATE TABLE insurance.agents ( agent_id text PRIMARY KEY, first_name text, last_name text, agency_name text, license_number text, license_state text, contact_email text, contact_phone text, hire_date date, termination_date date, status text, commission_rate numeric, manager_id text )

[User] Get the total fuel cost per route, showing route_number and the sum of total_cost for all fuel logs associated with trips on that route.

[Assistant]
SELECT r.route_number,
       SUM(fl.total_cost) AS total_fuel_cost
FROM transportation.routes r
JOIN transportation.trips t ON r.route_id = t.route_id
JOIN transportation.fuel_logs fl ON t.trip_id = fl.trip_id
GROUP BY r.route_number;

[User] Show me all users and the posts they have created, including the user's username and the post content.

[Assistant]
SELECT u.username, p.post_id, p.content
FROM social_media.users u
JOIN social_media.posts p ON u.user_id = p.user_id;

[User] Actually, can you please also include the post creation time and only show posts that have a media attachment?

[Assistant]
SELECT u.username, p.post_id, p.content, p.created_at
FROM social_media.users u
JOIN social_media.posts p ON u.user_id = p.user_id
WHERE p.media_url IS NOT NULL AND p.media_url <> '';

[User] List all appointments, including their subject and start time, along with the name and status of the case they are linked to.

[Assistant] SELECT T1.subject, T1.start_time, T2.case_name, T2.status FROM appointments AS T1 JOIN cases AS T2 ON T1.case_id = T2.case_id

[User] List all payments processed in USD, showing payment_id, guest_id, amount, and payment_timestamp.

[Assistant]
SELECT payment_id,
       guest_id,
       amount,
       payment_timestamp
FROM hospitality_technology.payments
WHERE currency_code = 'USD';

[User] Actually, only include those with amount greater than 1000.

[Assistant]
SELECT payment_id,
       guest_id,
       amount,
       payment_timestamp
FROM hospitality_technology.payments
WHERE currency_code = 'USD'
  AND amount > 1000;

[User] Also, order the results by amount descending and limit to the top 5.

[Assistant]
SELECT payment_id,
       guest_id,
       amount,
       payment_timestamp
FROM hospitality_technology.payments
WHERE currency_code = 'USD'
  AND amount > 1000
ORDER BY amount DESC
LIMIT 5;

[User] List the product ID, product name, and base premium for all insurance products created in 2022.

[Assistant]
SELECT product_id, product_name, base_premium
FROM insurance.insurance_products
WHERE EXTRACT(YEAR FROM created_at) = 2022;


System:
You are an expert in writing database language. You can write a corresponding database language query to answer the user's question based on the table structure described by the table creation statement. ##Table Structure
CREATE TABLE government_services.services ( service_id text PRIMARY KEY, agency_id text, service_name text, description text, category text, eligibility_criteria text, standard_fee numeric, average_processing_time_days int, is_active boolean, online_application_url text )
CREATE TABLE government_services.service_locations ( location_id text PRIMARY KEY, agency_id text, location_name text, address text, city text, state text, postal_code text, latitude numeric, longitude numeric, operating_hours text, contact_phone text, is_accessible boolean )
CREATE TABLE government_services.notifications ( notification_id character varying(64) NOT NULL, citizen_id character varying(64) NOT NULL, application_id character varying(64), message_subject character varying(255), message_body text NOT NULL, channel character varying(30) NOT NULL, sent_at timestamp NOT NULL, status character varying(30) NOT NULL, related_entity_type character varying(50), related_entity_id character varying(64), PRIMARY KEY (notification_id) )
##Table Structure
CREATE TABLE blockchain.blocks ( block_id character varying(64) NOT NULL, previous_block_id character varying(64), timestamp timestamp NOT NULL, nonce integer NOT NULL, merkle_root character varying(128) NOT NULL, difficulty integer NOT NULL, PRIMARY KEY (block_id) )
##Table Structure
CREATE TABLE legal_services.appointments ( appointment_id.text, client_id.text, lawyer_id.text, case_id.text, start_time.timestamp, end_time.timestamp, location.text, subject.text, notes.text, status.text, created_at.timestamp )
##Table Structure
CREATE TABLE insurance.agents ( agent_id.text, first_name.text, last_name.text, agency_name.text, license_number.text, license_state.text, contact_email.text, contact_phone.text, hire_date.date, termination_date.date, status.text, commission_rate.numeric, manager_id.text )
CREATE TABLE insurance.claim_documents ( document_id.text, claim_id.text, document_type.text, file_name.text, file_path.text, file_size_bytes.integer, mime_type.text, uploaded_by.text, uploaded_at.timestamp, description.text )
##Table Structure
CREATE TABLE trading_platform.wallets ( wallet_id text PRIMARY KEY, user_id text, address text, private_key text, created_at timestamp )
CREATE TABLE trading_platform.orders ( order_id text PRIMARY KEY, user_id text, wallet_id text, asset_id text, order_type text, quantity numeric, price numeric, status text, created_at timestamp )
CREATE TABLE trading_platform.trades (
    trade_id character varying(64) NOT NULL,  -- unique identifier for the trade
    order_id character varying(64) NOT NULL, -- identifier of the order that led to the trade
    buyer_id character varying(64) NOT NULL, -- identifier of the buyer
    seller_id character varying(64) NOT NULL, -- identifier of the seller
    asset_id character varying(64) NOT NULL, -- identifier of the asset being traded
    quantity numeric(38,14) NOT NULL, -- quantity of the asset in the trade
    price numeric(38,14) NOT NULL, -- price per unit of the asset
    traded_at timestamp NOT NULL, -- time when the trade was executed
    PRIMARY KEY (trade_id)
)
CREATE TABLE trading_platform.utxos ( utxo_id.text, transaction_id.text, output_index.integer, address.text, amount.numeric, spent.boolean )
CREATE TABLE trading_platform.dapps ( dapp_id character varying(64) NOT NULL, name character varying(128) NOT NULL, description text NOT NULL, url character varying(256) NOT NULL, PRIMARY KEY (dapp_id) )
##Table Structure
CREATE TABLE hospitality_technology.properties ( property_id text PRIMARY KEY, property_name text, address_line1 text, address_line2 text, city text, state_province text, postal_code text, country_code text, phone_number text, email_address text, property_type text, star_rating numeric, timezone text, manager_staff_id text, created_at timestamp, updated_at timestamp )
CREATE TABLE hospitality_technology.rooms ( room_id text PRIMARY KEY, property_id text, room_number text, room_type_id text, floor int, status text, is_smoking boolean, features text, current_condition text, last_cleaned_at timestamp )
##Table Structure
CREATE TABLE government_services.employees (
    employee_id character varying(64) NOT NULL, -- unique identifier for the government employee
    agency_id character varying(64) NOT NULL, -- FK to agencies table
    first_name character varying(100) NOT NULL,
    last_name character varying(100) NOT NULL,
    job_title character varying(150) NOT NULL,
    department character varying(100),
    work_email character varying(128) NOT NULL UNIQUE,
    work_phone character varying(32),
    hire_date date NOT NULL,
    termination_date date, -- null if currently employed
    access_level character varying(50), -- Role or permission level
    manager_employee_id character varying(64), -- FK to self for reporting structure
    PRIMARY KEY (employee_id)
)
##Table Structure
CREATE TABLE government_services.services ( service_id.text, agency_id.text, service_name.text, description.text, category.text, eligibility_criteria.text, standard_fee.numeric, average_processing_time_days.integer, is_active.boolean, online_application_url.text )
##Table Structure
CREATE TABLE government_services.agencies ( agency_id text, agency_name text, jurisdiction_level text, primary_contact_email text, main_phone_number text, website_url text, established_date date, parent_agency_id text )

[User] Which services have the longest average processing times? List the top 5 services by average processing time.

[Assistant]
SELECT
  service_name,
  average_processing_time_days
FROM
  government_services.services
ORDER BY
  average_processing_time_days DESC
LIMIT 5;

[User] Find all pairs of distinct block IDs that were mined at the exact same timestamp. Show both block IDs and the shared timestamp.

[Assistant] SELECT t1.block_id AS block_id_1, t2.block_id AS block_id_2, t1.timestamp FROM blockchain.blocks AS t1 JOIN blockchain.blocks AS t2 ON t1.timestamp = t2.timestamp WHERE t1.block_id < t2.block_id;

[User] Show me all appointments where the lawyer_id matches the client_id, and display the appointment_id, start_time, and status.

[Assistant] SELECT appointment_id, start_time, status FROM legal_services.appointments WHERE lawyer_id = client_id;

[User] Find the average commission rate among all agents whose hire date is after '2020-01-01'.

[Assistant] SELECT AVG(commission_rate) FROM insurance.agents WHERE hire_date > '2020-01-01';

[User] Show each user ID with the date of their first created wallet.

[Assistant]
SELECT user_id, MIN(created_at) AS first_wallet_date
FROM trading_platform.wallets
GROUP BY user_id;

[User] Get all non-smoking rooms with status 'Available'.

[Assistant]
SELECT room_id, property_id, room_number, floor
FROM hospitality_technology.rooms
WHERE is_smoking = FALSE
  AND status = 'Available';

[User] Now include the property_name for each room.

[Assistant]
SELECT r.room_id, r.room_number, p.property_name, r.floor
FROM hospitality_technology.rooms r
JOIN hospitality_technology.properties p
  ON r.property_id = p.property_id
WHERE r.is_smoking = FALSE
  AND r.status = 'Available';

[User] List the first name and last name of each employee, along with the first and last name of their manager.

[Assistant] SELECT e.first_name AS employee_first_name, e.last_name AS employee_last_name, m.first_name AS manager_first_name, m.last_name AS manager_last_name FROM government_services.employees AS e LEFT JOIN government_services.employees AS m ON e.manager_employee_id = m.employee_id;

[User] Can you show me a list of all active services along with their agency IDs and categories?

[Assistant] SELECT service_id, agency_id, service_name, category FROM government_services.services WHERE is_active = TRUE;

[User] Actually, only include services where the standard fee is less than 50.

[Assistant] SELECT service_id, agency_id, service_name, category FROM government_services.services WHERE is_active = TRUE AND standard_fee < 50;

[User] Can you show me a list of all agencies along with their parent agency names?

[Assistant]
SELECT a.agency_id, a.agency_name, pa.agency_name AS parent_agency_name
FROM government_services.agencies a
LEFT JOIN government_services.agencies pa ON a.parent_agency_id = pa.agency_id;

[User] Only show agencies that actually have a parent agency.

[Assistant]
SELECT a.agency_id, a.agency_name, pa.agency_name AS parent_agency_name
FROM government_services.agencies a
INNER JOIN government_services.agencies pa ON a.parent_agency_id = pa.agency_id;


System:
You are an expert in writing database language. You can write a corresponding database language query to answer the user's question based on the table structure described by the table creation statement. ##Table Structure
CREATE TABLE insurance.agents ( agent_id text PRIMARY KEY, first_name text, last_name text, agency_name text, license_number text, license_state text, contact_email text, contact_phone text, hire_date date, termination_date date, status text, commission_rate numeric, manager_id text )
##Table Structure
CREATE TABLE social_media.users ( user_id text PRIMARY KEY, username text, email text, password_hash text, full_name text, profile_picture_url text, bio text, location text, created_at timestamp, updated_at timestamp, is_verified bool )
CREATE TABLE social_media.hashtags ( hashtag_id text PRIMARY KEY, tag_name text, created_at timestamp )
CREATE TABLE social_media.messages ( message_id text PRIMARY KEY, conversation_id text, sender_user_id text, content text, media_url text, media_type text, sent_at timestamp, read_at timestamp )
CREATE TABLE social_media.conversations ( conversation_id text PRIMARY KEY, created_at timestamp, last_message_at timestamp, is_group_chat bool, group_name text )
CREATE TABLE social_media.user_settings ( setting_id text PRIMARY KEY, user_id text, theme text, email_notifications_enabled bool, push_notifications_enabled bool, private_profile bool, updated_at timestamp )
##Table Structure
CREATE TABLE government_services.documents ( document_id character varying(64) NOT NULL, application_id character varying(64), citizen_id character varying(64) NOT NULL, document_type character varying(100) NOT NULL, file_reference text NOT NULL, upload_timestamp timestamp NOT NULL, expiry_date date, verification_status character varying(30) DEFAULT 'Pending', verified_by_employee_id character varying(64), verification_timestamp timestamp, PRIMARY KEY (document_id) )
CREATE TABLE government_services.service_locations ( location_id character varying(64) NOT NULL, agency_id character varying(64) NOT NULL, location_name character varying(200), address text NOT NULL, city character varying(100), state character varying(50), postal_code character varying(20), latitude numeric(9, 6), longitude numeric(9, 6), operating_hours text, contact_phone character varying(32), is_accessible boolean, PRIMARY KEY (location_id) )
##Table Structure
CREATE TABLE legal_services.appointments ( appointment_id.text, client_id.text, lawyer_id.text, case_id.text, start_time.timestamp, end_time.timestamp, location.text, subject.text, notes.text, status.text, created_at.timestamp )
##Table Structure
CREATE TABLE web3.tokens ( token_id character varying(64) NOT NULL, contract_address character varying(128) NOT NULL, token_name character varying(128) NOT NULL, token_symbol character varying(32) NOT NULL, decimals integer NOT NULL, total_supply numeric(38,14) NOT NULL, PRIMARY KEY (token_id) )
##Table Structure
CREATE TABLE healthcare.doctors ( doctor_id text, first_name text, last_name text, specialty text, license_number text, phone_number text, email text, hospital_affiliation_id text, created_at timestamp, updated_at timestamp )
CREATE TABLE healthcare.appointments (
    appointment_id character varying(64) NOT NULL, -- unique identifier for the appointment
    patient_id character varying(64) NOT NULL, -- FK to patients table
    doctor_id character varying(64) NOT NULL, -- FK to doctors table
    appointment_time timestamp with time zone NOT NULL, -- date and time of the appointment
    duration_minutes integer NOT NULL, -- expected duration in minutes
    reason text, -- reason for the visit
    status character varying(32) NOT NULL, -- e.g., Scheduled, Completed, Cancelled, No-show
    location_id character varying(64), -- FK to a potential locations/clinics table
    notes text, -- notes related to scheduling
    created_at timestamp with time zone NOT NULL DEFAULT current_timestamp,
    PRIMARY KEY (appointment_id)
)
CREATE TABLE healthcare.medical_records ( record_id text PRIMARY KEY, patient_id text, appointment_id text, doctor_id text, record_date timestamp, chief_complaint text, present_illness_history text, past_medical_history text, physical_examination_notes text, assessment text, treatment_plan text, vitals text, created_at timestamp )
CREATE TABLE healthcare.diagnoses ( diagnosis_id character varying(64) NOT NULL, record_id character varying(64) NOT NULL, patient_id character varying(64) NOT NULL, doctor_id character varying(64) NOT NULL, diagnosis_code character varying(20) NOT NULL, code_type character varying(10) NOT NULL DEFAULT 'ICD-10', description text, diagnosis_date date NOT NULL, status character varying(32) NOT NULL, is_chronic boolean DEFAULT false, PRIMARY KEY (diagnosis_id) )
CREATE TABLE healthcare.medications (
    medication_id character varying(64) NOT NULL, -- unique identifier for the medication type
    medication_name character varying(255) NOT NULL, -- common or brand name
    generic_name character varying(255), -- generic chemical name
    manufacturer character varying(100), -- drug manufacturer
    ndc_code character varying(20) UNIQUE, -- National Drug Code (optional but useful)
    description text, -- description of the medication
    PRIMARY KEY (medication_id)
)
CREATE TABLE healthcare.prescriptions ( prescription_id text, record_id text, patient_id text, doctor_id text, medication_id text, dosage text, frequency text, route text, start_date date, end_date date, quantity_dispensed numeric, refills_allowed integer, prescription_date timestamp )
CREATE TABLE healthcare.insurance_plans ( plan_id.text, plan_name.text, insurance_provider.text, plan_type.text, contact_phone.text, website.text )
CREATE TABLE healthcare.patient_insurance ( patient_insurance_id text, patient_id text, plan_id text, policy_number text, group_number text, subscriber_name text, effective_date date, expiration_date date, is_primary boolean )
##Table Structure
CREATE TABLE transportation.drivers ( driver_id.text, employee_id.text, first_name.text, last_name.text, license_number.text, license_expiry_date.date, contact_number.text, email.text, hire_date.date, status.text )

[User] List all agents and their managers' full names.

[Assistant] SELECT a.first_name, a.last_name, m.first_name AS manager_first_name, m.last_name AS manager_last_name FROM insurance.agents a LEFT JOIN insurance.agents m ON a.manager_id = m.agent_id;

[User] Show the usernames of all users who were created in 2024.

[Assistant]
SELECT username
FROM social_media.users
WHERE EXTRACT(YEAR FROM created_at) = 2024;

[User] List all document IDs and their corresponding location names for documents that are associated with applications assigned to a service location in the city of 'Los Angeles'.

[Assistant]
SELECT d.document_id, sl.location_name
FROM government_services.documents d
JOIN government_services.service_locations sl
  ON d.application_id = sl.location_id
WHERE sl.city = 'Los Angeles';

[User] Find all pairs of appointments that are scheduled for the same case and overlap in time. Show the IDs of the two overlapping appointments and the shared case ID.

[Assistant] SELECT t1.appointment_id AS appointment1_id, t2.appointment_id AS appointment2_id, t1.case_id FROM legal_services.appointments AS t1 JOIN legal_services.appointments AS t2 ON t1.case_id = t2.case_id AND t1.appointment_id != t2.appointment_id WHERE t1.start_time < t2.end_time AND t2.start_time < t1.end_time;

[User] List all pairs of tokens (show token_id for both) that share the same contract address, excluding pairs where the token_id is the same.

[Assistant] SELECT t1.token_id AS token_id1, t2.token_id AS token_id2, t1.contract_address FROM web3.tokens AS t1 JOIN web3.tokens AS t2 ON t1.contract_address = t2.contract_address WHERE t1.token_id < t2.token_id;

[User] For each medication manufacturer, show the total number of distinct generic names they produce.

[Assistant] SELECT manufacturer, COUNT(DISTINCT generic_name) AS distinct_generic_name_count FROM healthcare.medications WHERE generic_name IS NOT NULL AND manufacturer IS NOT NULL GROUP BY manufacturer ORDER BY manufacturer;

[User] List pairs of drivers whose license expiry dates fall within 30 days of each other. Show both driver_ids, names, and the two expiry dates.

[Assistant] SELECT d1.driver_id AS driver1_id, d1.first_name AS driver1_first, d1.last_name AS driver1_last, d1.license_expiry_date AS expiry1, d2.driver_id AS driver2_id, d2.first_name AS driver2_first, d2.last_name AS driver2_last, d2.license_expiry_date AS expiry2 FROM transportation.drivers d1 JOIN transportation.drivers d2 ON d1.driver_id < d2.driver_id AND ABS((d1.license_expiry_date - d2.license_expiry_date)) <= INTERVAL '30 days';


System:
You are an expert in writing database language. You can write a corresponding database language query to answer the user's question based on the table structure described by the table creation statement. ##Table Structure
// Node Label: :Station
// Properties:
//   station_id: String (Constraint: UNIQUE)
//   station_name: String
//   city: String (Index recommended)
//   state_province: String
//   country_code: String
//   address: String
//   timezone: String
//   number_of_platforms: Integer
//   created_at: DateTime
//   last_updated_at: DateTime
// Example Cypher CREATE:
// CREATE (:Station {station_id: 'station_xyz', station_name: 'Grand Central Terminal', city: 'New York', ...})
// Node Label: :Platform
// Properties:
//   platform_id: String (Constraint: UNIQUE)
//   platform_number: String
//   track_number: String
//   status: String
//   length_meters: Float
//   accessible: Boolean
// Relationship: (:Platform)-[:LOCATED_AT]->(:Station)
// Example Cypher CREATE:
// MATCH (s:Station {station_id: 'station_xyz'})
// CREATE (p:Platform {platform_id: 'plat_123', ...})-[:LOCATED_AT]->(s)
// Node Label: :Train
// Properties:
//   train_id: String (Constraint: UNIQUE)
//   train_number: String (Constraint: UNIQUE)
//   model: String
//   manufacturer: String
//   year_manufactured: Integer
//   capacity: Integer
//   status: String
//   last_maintenance_date: Date
//   next_maintenance_date: Date
// Example Cypher CREATE:
// CREATE (:Train {train_id: 'train_789', train_number: 'Acela 2151', ...})
// Node Label: :TrainCar
// Properties:
//   car_id: String (Constraint: UNIQUE)
//   car_number: String
//   car_type: String
//   class: String
//   capacity: Integer
//   features: String (Or List<String> if driver supports)
// Relationship: (:TrainCar)-[:PART_OF_TRAIN]->(:Train)
// Example Cypher CREATE:
// MATCH (t:Train {train_id: 'train_789'})
// CREATE (c:TrainCar {car_id: 'car_abc', ...})-[:PART_OF_TRAIN]->(t)
// Relationship: (:Route)-[rel:HAS_STOP]->(:Station)
// Relationship Properties on :HAS_STOP:
//   sequence_order: Integer
//   distance_from_previous_km: Float
//   typical_stop_duration_minutes: Integer
// Example Cypher CREATE:
// MATCH (r:Route {route_id: 'route_ne_corr'}), (s:Station {station_id: 'station_pvd'})
// CREATE (r)-[:HAS_STOP {sequence_order: 2, distance_from_previous_km: 70.5, ...}]->(s)
// Node Label: :Passenger
// Properties:
//   passenger_id: String (Constraint: UNIQUE)
//   first_name: String
//   last_name: String
//   email: String (Constraint: UNIQUE, if not null)
//   phone_number: String (Constraint: UNIQUE, if not null)
//   date_of_birth: Date
//   loyalty_program_id: String
//   created_at: DateTime
// Example Cypher CREATE:
// CREATE (:Passenger {passenger_id: 'pass_pqr', first_name: 'Alice', ...})
// Node Label: :Booking
// Properties:
//   booking_id: String (Constraint: UNIQUE)
//   booking_datetime: DateTime
//   status: String
//   total_price: Float
//   currency_code: String
//   special_requests: String
// Relationships:
//   (:Passenger)-[:MADE_BOOKING]->(:Booking)
//   (:Booking)-[:FOR_TRIP]->(:ScheduledTrip)
// Example Cypher CREATE:
// MATCH (p:Passenger {passenger_id: 'pass_pqr'}), (sched:ScheduledTrip {schedule_id: 'sched_1122'})
// CREATE (p)-[:MADE_BOOKING]->(b:Booking {booking_id: 'book_zyx', ...})-[:FOR_TRIP]->(sched)
// Node Label: :Staff
// Properties:
//   staff_id: String (Constraint: UNIQUE)
//   first_name: String
//   last_name: String
//   role: String
//   employee_number: String (Constraint: UNIQUE)
//   hire_date: Date
//   contact_email: String (Constraint: UNIQUE, if not null)
//   contact_phone: String
//   is_active: Boolean
// Relationship (Optional):
//   (:Staff)-[:BASED_AT]->(:Station)
// Example Cypher CREATE:
// CREATE (:Staff {staff_id: 'staff_mno', first_name: 'Bob', ...})
// OPTIONAL MATCH (s:Station {station_id: 'station_xyz'}) // If primary_station_id exists
// WITH s, staff_mno // Need to get the created staff node reference
// WHERE s IS NOT NULL
// CREATE (staff_mno)-[:BASED_AT]->(s)
##Table Structure
CREATE TABLE hospitality_technology.rooms ( room_id.text, property_id.text, room_number.text, room_type_id.text, floor.integer, status.text, is_smoking.boolean, features.text, current_condition.text, last_cleaned_at.timestamp )
CREATE TABLE hospitality_technology.staff ( staff_id.text, property_id.text, first_name.text, last_name.text, position.text, work_email.text, work_phone.text, hire_date.date, termination_date.date, is_active.boolean, access_level.integer, manager_id.text, created_at.timestamp )
CREATE TABLE hospitality_technology.services ( service_id.text, property_id.text, service_name.text, description.text, category.text, price.numeric, unit.text, is_available.boolean, department.text )
CREATE TABLE hospitality_technology.reviews ( review_id.text, property_id.text, reservation_id.text, guest_id.text, rating_overall.integer, rating_cleanliness.integer, rating_service.integer, rating_location.integer, rating_value.integer, comment.text, review_source.text, review_date.timestamp, is_public.boolean, staff_response.text, response_staff_id.text, response_date.timestamp )
##Table Structure
CREATE TABLE blockchain.smart_contracts ( contract_id text, creator_address text, code text, timestamp timestamp )
##Table Structure
CREATE TABLE trading_platform.dapps ( dapp_id.text, name.text, description.text, url.text )

[User] Can you retrieve the total number of train cars for each train in the database?

[Assistant]
MATCH (t:Train)<-[:PART_OF_TRAIN]-(tc:TrainCar)
RETURN t.train_id, t.train_number, COUNT(tc) AS total_cars
ORDER BY t.train_id

[User] Find the top 3 staff members who have responded to the most public reviews. Include their staff_id, first_name, last_name, and the count of responses.

[Assistant]
SELECT
  s.staff_id,
  s.first_name,
  s.last_name,
  COUNT(*) AS response_count
FROM hospitality_technology.staff AS s
JOIN hospitality_technology.reviews AS r
  ON s.staff_id = r.response_staff_id
WHERE r.is_public = TRUE
  AND r.response_staff_id IS NOT NULL
GROUP BY s.staff_id, s.first_name, s.last_name
ORDER BY response_count DESC
LIMIT 3;

[User] Show me all smart contracts created by addresses that have created more than 3 contracts, along with the total number of contracts each creator has made.

[Assistant]
SELECT sc.contract_id, sc.creator_address, COUNT(*) OVER (PARTITION BY sc.creator_address) AS total_contracts
FROM blockchain.smart_contracts sc
WHERE sc.creator_address IN (
    SELECT creator_address
    FROM blockchain.smart_contracts
    GROUP BY creator_address
    HAVING COUNT(*) > 3
)
ORDER BY total_contracts DESC;

[User] Now filter these results to only show contracts created in the last 6 months.

[Assistant]
SELECT sc.contract_id, sc.creator_address, COUNT(*) OVER (PARTITION BY sc.creator_address) AS total_contracts
FROM blockchain.smart_contracts sc
WHERE sc.creator_address IN (
    SELECT creator_address
    FROM blockchain.smart_contracts
    GROUP BY creator_address
    HAVING COUNT(*) > 3
)
AND sc.timestamp >= NOW() - INTERVAL '6 months'
ORDER BY total_contracts DESC;

[User] Show all DApps whose name starts with the letter 'C'.

[Assistant] SELECT * FROM trading_platform.dapps WHERE name ILIKE 'C%';

[User] Could you instead make it case-sensitive so only names that start with an uppercase 'C' are included?

[Assistant] SELECT * FROM trading_platform.dapps WHERE name LIKE 'C%';

[User] Actually, just show their names and descriptions.

[Assistant] SELECT name, description FROM trading_platform.dapps WHERE name LIKE 'C%';

[User] Add the URL in the result too, and order by name alphabetically.

[Assistant] SELECT name, description, url FROM trading_platform.dapps WHERE name LIKE 'C%' ORDER BY name ASC;


System:
You are an expert in writing database language. You can write a corresponding database language query to answer the user's question based on the table structure described by the table creation statement. ##Table Structure
CREATE TABLE insurance.policies ( policy_id.text, customer_id.text, product_id.text, agent_id.text, policy_number.text, start_date.date, end_date.date, premium_amount.numeric, coverage_limit.numeric, deductible.numeric, status.text, issued_at.timestamp, cancellation_date.date, cancellation_reason.text )
##Table Structure
CREATE TABLE project_fundraising_record ( id.text, project_id.text, project_name.text, rounds_name.text, investment_value.numeric, investment_date.text, introduction.text, valuation.numeric )
##Table Structure
CREATE TABLE social_media.posts ( post_id character varying(64) NOT NULL, user_id character varying(64) NOT NULL, content text, media_url text, media_type character varying(20), created_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, updated_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, visibility character varying(20) NOT NULL DEFAULT 'public', location_lat numeric(9,6), location_lon numeric(9,6), PRIMARY KEY (post_id) )
CREATE TABLE social_media.likes ( like_id text PRIMARY KEY, user_id text, post_id text, comment_id text, created_at timestamp )
CREATE TABLE social_media.hashtags ( hashtag_id character varying(64) NOT NULL, tag_name character varying(100) NOT NULL UNIQUE, created_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, PRIMARY KEY (hashtag_id) )
CREATE TABLE social_media.messages (
    message_id character varying(64) NOT NULL, -- unique identifier for the message
    conversation_id character varying(64) NOT NULL, -- identifier for the conversation thread (FK to conversations.conversation_id)
    sender_user_id character varying(64) NOT NULL, -- identifier of the sender (FK to users.user_id)
    content text, -- textual content of the message
    media_url text, -- URL to attached media (image/video)
    media_type character varying(20), -- type of media ('image', 'video', null)
    sent_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, -- timestamp when message was sent
    read_at timestamp, -- timestamp when message was read by recipient(s)
    PRIMARY KEY (message_id)
)
CREATE TABLE social_media.conversation_participants ( participant_id.text, conversation_id.text, user_id.text, joined_at.timestamp, last_read_at.timestamp )
##Table Structure
CREATE TABLE insurance.agents ( agent_id character varying(64) NOT NULL, first_name character varying(100) NOT NULL, last_name character varying(100) NOT NULL, agency_name character varying(150), license_number character varying(100) NOT NULL UNIQUE, license_state character varying(50) NOT NULL, contact_email character varying(128) UNIQUE, contact_phone character varying(30), hire_date date, termination_date date, status character varying(20) NOT NULL DEFAULT 'Active', commission_rate numeric(5, 4) NOT NULL DEFAULT 0.05, manager_id character varying(64), PRIMARY KEY (agent_id) )
##Table Structure
CREATE TABLE hospitality_technology.room_types ( room_type_id.text, property_id.text, type_name.text, description.text, base_rate.numeric, max_occupancy.integer, bed_type.text, area_sqft.numeric, amenities.text )
##Table Structure
CREATE TABLE transportation.maintenance_logs ( log_id character varying(64) NOT NULL, vehicle_id character varying(64) NOT NULL, service_date date NOT NULL, odometer_reading integer, service_type character varying(128) NOT NULL, description text NOT NULL, cost numeric(10, 2), mechanic_name character varying(128), next_service_due_date date, PRIMARY KEY (log_id) )
##Table Structure
CREATE TABLE web3.transactions ( transaction_id character varying(64) NOT NULL, from_address character varying(128) NOT NULL, to_address character varying(128), value numeric(38,14) NOT NULL, gas_used integer NOT NULL, gas_price numeric(38,14) NOT NULL, block_number integer NOT NULL, timestamp timestamp NOT NULL, input_data text, status character varying(32) NOT NULL, nonce integer NOT NULL, PRIMARY KEY (transaction_id) )
CREATE TABLE web3.token_transfers (
    transfer_id character varying(64) NOT NULL,  -- unique identifier for the transfer
    token_id character varying(64) NOT NULL, -- identifier of the token being transferred
    from_address character varying(128) NOT NULL, -- address of the sender
    to_address character varying(128) NOT NULL, -- address of the receiver
    value numeric(38,14) NOT NULL, -- amount of tokens transferred
    transaction_id character varying(64) NOT NULL, -- identifier of the transaction containing the transfer
    log_index integer NOT NULL, -- index of the transfer log in the transaction
    PRIMARY KEY (transfer_id)
)
##Table Structure
CREATE TABLE healthcare.medical_records ( record_id text PRIMARY KEY, patient_id text, appointment_id text, doctor_id text, record_date timestamp, chief_complaint text, present_illness_history text, past_medical_history text, physical_examination_notes text, assessment text, treatment_plan text, vitals text, created_at timestamp )

[User] List all policies that expired in the last 30 days, along with their product IDs and premium amounts.

[Assistant] SELECT policy_id, product_id, premium_amount FROM insurance.policies WHERE end_date BETWEEN DATE_SUB(CURRENT_DATE, INTERVAL 30 DAY) AND CURRENT_DATE AND status = 'expired';

[User] Now include only policies that had a deductible of $1000 or more.

[Assistant] SELECT policy_id, product_id, premium_amount, deductible FROM insurance.policies WHERE end_date BETWEEN DATE_SUB(CURRENT_DATE, INTERVAL 30 DAY) AND CURRENT_DATE AND status = 'expired' AND deductible >= 1000;

[User] Which projects raised funds in January 2022?

[Assistant] SELECT project_name, rounds_name, investment_value, investment_date FROM project_fundraising_record WHERE investment_date >= '2022-01-01' AND investment_date < '2022-02-01';

[User] Please also show their introductions.

[Assistant] SELECT project_name, rounds_name, investment_value, investment_date, introduction FROM project_fundraising_record WHERE investment_date >= '2022-01-01' AND investment_date < '2022-02-01';

[User] How many distinct users have sent messages in each conversation? Return conversation_id and user_count.

[Assistant]
SELECT conversation_id,
       COUNT(DISTINCT sender_user_id) AS user_count
FROM social_media.messages
GROUP BY conversation_id;

[User] Which agents, along with their managers' full names, are licensed in 'TX' and are currently active?

[Assistant]
SELECT a.agent_id, a.first_name AS agent_first_name, a.last_name AS agent_last_name, m.first_name AS manager_first_name, m.last_name AS manager_last_name
FROM insurance.agents a
LEFT JOIN insurance.agents m ON a.manager_id = m.agent_id
WHERE a.license_state = 'TX' AND a.status = 'Active';

[User] Show all room types that offer 'WiFi' in their amenities.

[Assistant] SELECT room_type_id, property_id, type_name, amenities FROM hospitality_technology.room_types WHERE amenities LIKE '%WiFi%';

[User] Only include those with a base rate below 100 and return the results sorted by base_rate ascending.

[Assistant] SELECT room_type_id, property_id, type_name, amenities, base_rate FROM hospitality_technology.room_types WHERE amenities LIKE '%WiFi%' AND base_rate < 100 ORDER BY base_rate ASC;

[User] Show all maintenance logs where the 'next_service_due_date' is before the current date, including the log ID, service date, service type, and the overdue next service date.

[Assistant] SELECT log_id, service_date, service_type, next_service_due_date FROM transportation.maintenance_logs WHERE next_service_due_date < CURRENT_DATE;

[User] Show the top 5 transactions with the highest number of token transfers, along with their Ethereum value. Include transaction_id, token_transfer_count, and ether_value.

[Assistant]
SELECT
  tt.transaction_id,
  COUNT(tt.transfer_id) AS token_transfer_count,
  t.value AS ether_value
FROM web3.token_transfers tt
JOIN web3.transactions t
  ON tt.transaction_id = t.transaction_id
GROUP BY
  tt.transaction_id,
  t.value
ORDER BY token_transfer_count DESC
LIMIT 5;

[User] Show me all medical records created before January 1, 2022.

[Assistant] SELECT * FROM healthcare.medical_records WHERE record_date < '2022-01-01';


System:
You are an expert in writing database language. You can write a corresponding database language query to answer the user's question based on the table structure described by the table creation statement. ##Table Structure
CREATE TABLE government_services.applications ( application_id text PRIMARY KEY, citizen_id text, service_id text, submitted_at timestamp, status text, last_updated_at timestamp, assigned_employee_id text, decision_date date, notes text, reference_number text )
##Table Structure
CREATE TABLE government_services.services ( service_id text PRIMARY KEY, agency_id text, service_name text, description text, category text, eligibility_criteria text, standard_fee numeric, average_processing_time_days int, is_active boolean, online_application_url text )
CREATE TABLE government_services.documents ( document_id text PRIMARY KEY, application_id text, citizen_id text, document_type text, file_reference text, upload_timestamp timestamp, expiry_date date, verification_status text, verified_by_employee_id text, verification_timestamp timestamp )
##Table Structure
CREATE TABLE trading_platform.users (
    user_id character varying(64) NOT NULL,  -- unique identifier for the user
    username character varying(128) NOT NULL, -- username of the user
    email character varying(128) NOT NULL, -- email address of the user
    password_hash text NOT NULL, -- hashed password of the user
    created_at timestamp NOT NULL, -- time when the user account was created
    PRIMARY KEY (user_id)
)
CREATE TABLE trading_platform.orders (
    order_id character varying(64) NOT NULL,  -- unique identifier for the order
    user_id character varying(64) NOT NULL, -- identifier of the user placing the order
    wallet_id character varying(64) NOT NULL, -- identifier of the wallet used for the order
    asset_id character varying(64) NOT NULL, -- identifier of the asset being traded
    order_type character varying(32) NOT NULL, -- type of the order (e.g., buy, sell)
    quantity numeric(38,14) NOT NULL, -- quantity of the asset in the order
    price numeric(38,14) NOT NULL, -- price per unit of the asset
    status character varying(32) NOT NULL, -- status of the order (e.g., open, filled, canceled)
    created_at timestamp NOT NULL, -- time when the order was created
    PRIMARY KEY (order_id)
)
CREATE TABLE trading_platform.dapps (
    dapp_id character varying(64) NOT NULL,  -- unique identifier for the DApp
    name character varying(128) NOT NULL, -- name of the DApp
    description text NOT NULL, -- description of the DApp
    url character varying(256) NOT NULL, -- URL of the DApp
    PRIMARY KEY (dapp_id)
)
CREATE TABLE trading_platform.peers (
    peer_id character varying(64) NOT NULL,  -- unique identifier for the peer
    ip_address character varying(15) NOT NULL, -- IP address of the peer
    port integer NOT NULL, -- port number of the peer
    last_seen timestamp NOT NULL, -- last time the peer was active
    PRIMARY KEY (peer_id)
)
CREATE TABLE trading_platform.metadata (
    metadata_id character varying(64) NOT NULL,  -- unique identifier for the metadata
    asset_id character varying(64) NOT NULL, -- identifier of the asset the metadata is associated with
    key character varying(128) NOT NULL, -- key of the metadata
    value text NOT NULL, -- value of the metadata
    PRIMARY KEY (metadata_id)
)
CREATE TABLE trading_platform.logs (
    log_id character varying(64) NOT NULL,  -- unique identifier for the log entry
    user_id character varying(64), -- identifier of the user associated with the log entry
    action character varying(128) NOT NULL, -- action performed
    details text NOT NULL, -- details of the action
    logged_at timestamp NOT NULL, -- time when the log entry was created
    PRIMARY KEY (log_id)
)
##Table Structure
CREATE TABLE social_media.comments (
    comment_id character varying(64) NOT NULL, -- unique identifier for the comment
    post_id character varying(64) NOT NULL, -- identifier of the post being commented on (FK to posts.post_id)
    user_id character varying(64) NOT NULL, -- identifier of the user who made the comment (FK to users.user_id)
    parent_comment_id character varying(64), -- identifier of the parent comment if it's a reply (FK to comments.comment_id)
    content text NOT NULL, -- textual content of the comment
    created_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, -- timestamp of comment creation
    updated_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, -- timestamp of last comment edit
    PRIMARY KEY (comment_id)
)
CREATE TABLE social_media.likes ( like_id text, user_id text, post_id text, comment_id text, created_at timestamp )
CREATE TABLE social_media.conversations ( conversation_id text PRIMARY KEY, created_at timestamp, last_message_at timestamp, is_group_chat bool, group_name text )
##Table Structure
CREATE TABLE trading_platform.peers ( peer_id character varying(64) NOT NULL, ip_address character varying(15) NOT NULL, port integer NOT NULL, last_seen timestamp NOT NULL, PRIMARY KEY (peer_id) )

[User] Find all applications that were submitted in 2023 but received a decision ('Approved' or 'Rejected') in 2024. List the application ID, submitted date, decision date, and status.

[Assistant] SELECT application_id, submitted_at, decision_date, status FROM government_services.applications WHERE submitted_at BETWEEN '2023-01-01 00:00:00' AND '2023-12-31 23:59:59' AND status IN ('Approved', 'Rejected') AND decision_date BETWEEN '2024-01-01' AND '2024-12-31';

[User] What is the average processing time in days for active services?

[Assistant] SELECT AVG(average_processing_time_days) FROM government_services.services WHERE is_active = TRUE

[User] Could you show the average processing time only for active services where the standard fee is less than 50?

[Assistant] SELECT AVG(average_processing_time_days) FROM government_services.services WHERE is_active = TRUE AND standard_fee < 50

[User] How many documents have been uploaded for applications related to active services?

[Assistant] SELECT COUNT(T3.document_id) FROM government_services.services AS T1 JOIN applications AS T2 ON T1.service_id = T2.service_id JOIN government_services.documents AS T3 ON T2.application_id = T3.application_id WHERE T1.is_active = TRUE

[User] Only include documents with a verification status of 'Verified'.

[Assistant] SELECT COUNT(T3.document_id) FROM government_services.services AS T1 JOIN applications AS T2 ON T1.service_id = T2.service_id JOIN government_services.documents AS T3 ON T2.application_id = T3.application_id WHERE T1.is_active = TRUE AND T3.verification_status = 'Verified'

[User] For each asset, I want to know how many orders have the status 'filled', showing the asset symbol.

[Assistant]
SELECT m.value AS asset_symbol,
       COUNT(*) AS filled_order_count
FROM trading_platform.orders o
JOIN trading_platform.metadata m
  ON o.asset_id = m.asset_id
 AND m.key = 'symbol'
WHERE o.status = 'filled'
GROUP BY m.value;

[User] Include assets that have zero filled orders, showing filled_order_count as 0.

[Assistant]
WITH asset_symbols AS (
  SELECT DISTINCT asset_id,
         value AS asset_symbol
  FROM trading_platform.metadata
  WHERE key = 'symbol'
)
SELECT a.asset_symbol,
       COALESCE(f.filled_order_count, 0) AS filled_order_count
FROM asset_symbols a
LEFT JOIN (
  SELECT asset_id,
         COUNT(*) AS filled_order_count
  FROM trading_platform.orders
  WHERE status = 'filled'
  GROUP BY asset_id
) f
  ON a.asset_id = f.asset_id;

[User] List all comment IDs that have not received any likes.

[Assistant] SELECT T1.comment_id FROM social_media.comments AS T1 LEFT JOIN social_media.likes AS T2 ON T1.comment_id = T2.comment_id WHERE T2.like_id IS NULL;

[User] Can you also include the content of these comments and the post_id they belong to?

[Assistant] SELECT T1.comment_id, T1.content, T1.post_id FROM social_media.comments AS T1 LEFT JOIN social_media.likes AS T2 ON T1.comment_id = T2.comment_id WHERE T2.like_id IS NULL;

[User] List all peers whose IP address ends with '.255', showing their peer_id, ip_address, and last_seen timestamp.

[Assistant] SELECT peer_id, ip_address, last_seen FROM trading_platform.peers WHERE ip_address LIKE '%.255';

[User] From the list of peers whose IP ends with '.255', how many distinct port numbers are being used?

[Assistant] SELECT COUNT(DISTINCT port) FROM trading_platform.peers WHERE ip_address LIKE '%.255';


System:
You are an expert in writing database language. You can write a corresponding database language query to answer the user's question based on the table structure described by the table creation statement. ##Table Structure
CREATE TABLE social_media.post_hashtags ( post_hashtag_id text, post_id text, hashtag_id text )
CREATE TABLE social_media.conversations ( conversation_id text, created_at timestamp, last_message_at timestamp, is_group_chat boolean, group_name text )
CREATE TABLE social_media.notifications ( notification_id text, recipient_user_id text, sender_user_id text, notification_type text, target_entity_id text, target_entity_type text, created_at timestamp, read_at timestamp )
##Table Structure
CREATE TABLE transportation.fuel_logs (
    fuel_log_id character varying(64) NOT NULL,  -- unique identifier for the fuel log entry
    vehicle_id character varying(64) NOT NULL, -- identifier of the vehicle fueled
    trip_id character varying(64), -- optional: identifier of the trip during which fueling occurred
    log_timestamp timestamp with time zone NOT NULL, -- time when fueling occurred
    fuel_type character varying(32) NOT NULL, -- type of fuel added (matches vehicle's fuel type)
    quantity numeric(10, 3) NOT NULL, -- amount of fuel added (e.g., Liters, Gallons, kWh)
    unit character varying(16) NOT NULL, -- unit of quantity (e.g., L, gal, kWh)
    cost_per_unit numeric(8, 4), -- price per unit of fuel
    total_cost numeric(10, 2) NOT NULL, -- total cost of the fuel purchase
    odometer_reading integer, -- vehicle mileage at time of fueling
    location_id character varying(64), -- identifier of the fueling station/location
    PRIMARY KEY (fuel_log_id)
)
##Table Structure
CREATE TABLE hospitality_technology.reviews ( review_id text PRIMARY KEY, property_id text, reservation_id text, guest_id text, rating_overall int, rating_cleanliness int, rating_service int, rating_location int, rating_value int, comment text, review_source text, review_date timestamp, is_public boolean, staff_response text, response_staff_id text, response_date timestamp )
##Table Structure
CREATE TABLE web3.users (
    user_id character varying(64) NOT NULL,  -- unique identifier for the user
    username character varying(128) NOT NULL, -- username of the user
    email character varying(128) NOT NULL, -- email address of the user
    password_hash text NOT NULL, -- hashed password of the user
    created_at timestamp NOT NULL, -- time when the user account was created
    PRIMARY KEY (user_id)
)
##Table Structure
CREATE TABLE transportation.vehicles ( vehicle_id.text, license_plate.text, vin.text, make.text, model.text, year.integer, type.text, capacity.integer, fuel_type.text, status.text, depot_id.text, acquisition_date.date )
CREATE TABLE transportation.drivers ( driver_id.text, employee_id.text, first_name.text, last_name.text, license_number.text, license_expiry_date.date, contact_number.text, email.text, hire_date.date, status.text )
CREATE TABLE transportation.locations ( location_id.text, name.text, type.text, address_line1.text, city.text, state_province.text, postal_code.text, country.text, latitude.numeric, longitude.numeric, timezone.text )
CREATE TABLE transportation.fuel_logs ( fuel_log_id.text, vehicle_id.text, trip_id.text, log_timestamp.timestamp, fuel_type.text, quantity.numeric, unit.text, cost_per_unit.numeric, total_cost.numeric, odometer_reading.integer, location_id.text )
CREATE TABLE transportation.bookings ( booking_id.text, passenger_id.text, trip_id.text, seat_number.text, booking_time.timestamp, status.text, fare.numeric, payment_transaction_id.text, special_requests.text )
##Table Structure
CREATE TABLE web3.wallets ( wallet_id text, user_id text, address text, private_key text, created_at timestamp )
##Table Structure
CREATE TABLE hospitality_technology.services ( service_id character varying(64) NOT NULL, property_id character varying(64) NOT NULL, service_name character varying(150) NOT NULL, description text, category character varying(100), price numeric(10, 2) NOT NULL, unit character varying(30), is_available boolean NOT NULL DEFAULT true, department character varying(100), PRIMARY KEY (service_id), FOREIGN KEY (property_id) REFERENCES hospitality_technology.properties(property_id) )

[User] Get all notifications for posts tagged with hashtag 'H123', showing notification_id and created_at.

[Assistant]
SELECT n.notification_id, n.created_at
FROM social_media.notifications n
JOIN social_media.post_hashtags ph
  ON n.target_entity_type = 'post'
  AND n.target_entity_id = ph.post_id
WHERE ph.hashtag_id = 'H123';

[User] Now filter to only include notifications of type 'comment'.

[Assistant]
SELECT n.notification_id, n.created_at
FROM social_media.notifications n
JOIN social_media.post_hashtags ph
  ON n.target_entity_type = 'post'
  AND n.target_entity_id = ph.post_id
WHERE ph.hashtag_id = 'H123'
  AND n.notification_type = 'comment';

[User] For each fuel type, list the number of unique locations where fuel refueling occurred, and also show the total quantity refueled for that fuel type and location.

[Assistant]
SELECT fuel_type, location_id, COUNT(DISTINCT location_id) AS unique_location_count, SUM(quantity) AS total_quantity
FROM transportation.fuel_logs
GROUP BY fuel_type, location_id;

[User] Find all review comments that have a staff response, showing the comment and the staff response date.

[Assistant] SELECT comment, response_date FROM reviews WHERE response_date IS NOT NULL;

[User] Now, also include the name of the staff member who responded.

[Assistant] SELECT T1.comment, T1.response_date, T2.first_name, T2.last_name FROM reviews AS T1 JOIN staff AS T2 ON T1.response_staff_id = T2.staff_id WHERE T1.response_date IS NOT NULL;

[User] Further filter this list to only show responses made more than 24 hours after the review was submitted, and include the review date and the reservation ID.

[Assistant] SELECT T1.comment, T1.response_date, T2.first_name, T2.last_name, T1.review_date, T1.reservation_id FROM reviews AS T1 JOIN staff AS T2 ON T1.response_staff_id = T2.staff_id WHERE T1.response_date IS NOT NULL AND T1.response_date > T1.review_date + INTERVAL '24 hours';

[User] Count the number of users for each email domain.

[Assistant]
SELECT split_part(email, '@', 2) AS domain, COUNT(*) AS user_count
FROM web3.users
GROUP BY domain;

[User] Filter to domains with more than 5 users.

[Assistant]
SELECT split_part(email, '@', 2) AS domain, COUNT(*) AS user_count
FROM web3.users
GROUP BY domain
HAVING COUNT(*) > 5;

[User] Can you provide the total number of fuel refueling events and the sum of total_cost at each fueling location, including the location name and city?

[Assistant]
SELECT l.location_id, l.name, l.city, COUNT(fl.fuel_log_id) AS num_refuels, SUM(fl.total_cost) AS total_cost
FROM transportation.fuel_logs fl
JOIN transportation.locations l ON fl.location_id = l.location_id
GROUP BY l.location_id, l.name, l.city;

[User] For each user, what is the average time difference in days between their wallet creations? Return user_id and avg_diff_days.

[Assistant]
WITH diffs AS (
  SELECT
    user_id,
    EXTRACT(EPOCH FROM (created_at - LAG(created_at) OVER (PARTITION BY user_id ORDER BY created_at))) / 86400 AS diff_days
  FROM web3.wallets
)
SELECT
  user_id,
  AVG(diff_days) AS avg_diff_days
FROM diffs
WHERE diff_days IS NOT NULL
GROUP BY user_id;

[User] Actually, only include users who have created more than 2 wallets.

[Assistant]
WITH diffs AS (
  SELECT
    user_id,
    EXTRACT(EPOCH FROM (created_at - LAG(created_at) OVER (PARTITION BY user_id ORDER BY created_at))) / 86400 AS diff_days
  FROM web3.wallets
)
SELECT
  user_id,
  AVG(diff_days) AS avg_diff_days
FROM diffs
WHERE diff_days IS NOT NULL
GROUP BY user_id
HAVING COUNT(diff_days) > 1;

[User] List all available services along with the property name where they are offered.

[Assistant]
SELECT s.service_id, s.service_name, p.property_name
FROM hospitality_technology.services s
JOIN hospitality_technology.properties p ON s.property_id = p.property_id
WHERE s.is_available = true;


System:
You are an expert in writing database language. You can write a corresponding database language query to answer the user's question based on the table structure described by the table creation statement. ##Table Structure
CREATE TABLE hospitality_technology.payments ( payment_id text PRIMARY KEY, reservation_id text, guest_id text, bill_id text, amount numeric, currency_code text, payment_method text, card_type text, card_last_four text, transaction_ref text, payment_timestamp timestamp, status text, staff_id_processed text, notes text )
##Table Structure
CREATE TABLE insurance.policies ( policy_id text PRIMARY KEY, customer_id text, product_id text, agent_id text, policy_number text, start_date date, end_date date, premium_amount numeric, coverage_limit numeric, deductible numeric, status text, issued_at timestamp, cancellation_date date, cancellation_reason text )
CREATE TABLE insurance.insurance_products ( product_id text PRIMARY KEY, product_name text, product_type text, description text, base_premium numeric, coverage_details text, underwriting_rules text, is_active boolean, created_at timestamp, updated_at timestamp )
CREATE TABLE insurance.agents ( agent_id text PRIMARY KEY, first_name text, last_name text, agency_name text, license_number text, license_state text, contact_email text, contact_phone text, hire_date date, termination_date date, status text, commission_rate numeric, manager_id text )
##Table Structure
CREATE TABLE transportation.trips (
    trip_id character varying(64) NOT NULL,  -- unique identifier for a specific trip instance
    route_id character varying(64), -- identifier of the route being followed (can be null for ad-hoc trips)
    vehicle_id character varying(64) NOT NULL, -- identifier of the vehicle used
    driver_id character varying(64) NOT NULL, -- identifier of the driver operating
    scheduled_departure timestamp with time zone NOT NULL, -- planned departure time
    actual_departure timestamp with time zone, -- actual departure time
    scheduled_arrival timestamp with time zone NOT NULL, -- planned arrival time
    actual_arrival timestamp with time zone, -- actual arrival time
    origin_location_id character varying(64) NOT NULL, -- actual starting location (could differ from route origin)
    destination_location_id character varying(64) NOT NULL, -- actual ending location (could differ from route destination)
    status character varying(32) NOT NULL, -- e.g., Scheduled, In Progress, Completed, Delayed, Cancelled
    passenger_count integer, -- number of passengers (if applicable)
    cargo_manifest_id character varying(64), -- link to cargo details (if applicable)
    PRIMARY KEY (trip_id)
)
##Table Structure
CREATE TABLE transportation.fuel_logs (
    fuel_log_id character varying(64) NOT NULL,  -- unique identifier for the fuel log entry
    vehicle_id character varying(64) NOT NULL, -- identifier of the vehicle fueled
    trip_id character varying(64), -- optional: identifier of the trip during which fueling occurred
    log_timestamp timestamp with time zone NOT NULL, -- time when fueling occurred
    fuel_type character varying(32) NOT NULL, -- type of fuel added (matches vehicle's fuel type)
    quantity numeric(10, 3) NOT NULL, -- amount of fuel added (e.g., Liters, Gallons, kWh)
    unit character varying(16) NOT NULL, -- unit of quantity (e.g., L, gal, kWh)
    cost_per_unit numeric(8, 4), -- price per unit of fuel
    total_cost numeric(10, 2) NOT NULL, -- total cost of the fuel purchase
    odometer_reading integer, -- vehicle mileage at time of fueling
    location_id character varying(64), -- identifier of the fueling station/location
    PRIMARY KEY (fuel_log_id)
)
##Table Structure
CREATE TABLE legal_services.clients ( client_id text, first_name text, last_name text, company_name text, email text, phone text, address text, date_registered timestamp, status text )
CREATE TABLE legal_services.time_entries ( entry_id character varying(64) NOT NULL, case_id character varying(64) NOT NULL, lawyer_id character varying(64) NOT NULL, date_worked date NOT NULL, hours_spent numeric(5, 2) NOT NULL CHECK (hours_spent > 0), billing_rate numeric(10, 2) NOT NULL, description text NOT NULL, is_billable boolean DEFAULT true, is_billed boolean DEFAULT false, invoice_id character varying(64), created_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, PRIMARY KEY (entry_id) )
##Table Structure
CREATE TABLE hospitality_technology.service_orders ( order_id text PRIMARY KEY, reservation_id text, guest_id text, service_id text, staff_id_ordered text, staff_id_delivered text, order_timestamp timestamp, delivery_timestamp timestamp, quantity int, unit_price numeric, total_price numeric, status text, notes text, bill_id text )

[User] Find the total amount of payments and the number of payments for each status.

[Assistant]
SELECT status, SUM(amount) AS total_amount, COUNT(*) AS payment_count
FROM hospitality_technology.payments
GROUP BY status;

[User] Actually, could you also include the breakdown by payment method within each status?

[Assistant]
SELECT status, payment_method, SUM(amount) AS total_amount, COUNT(*) AS payment_count
FROM hospitality_technology.payments
GROUP BY status, payment_method;

[User] List all agents who have sold at least one policy for an insurance product of type 'Health'. For each agent, show their full name, agency name, and the product name.

[Assistant]
SELECT DISTINCT a.first_name || ' ' || a.last_name AS agent_full_name, a.agency_name, ip.product_name
FROM insurance.agents a
JOIN insurance.policies p ON a.agent_id = p.agent_id
JOIN insurance.insurance_products ip ON p.product_id = ip.product_id
WHERE ip.product_type = 'Health';

[User] List all trips that were completed and experienced a significant delay in actual arrival compared to the scheduled arrival (more than 45 minutes).

[Assistant]
SELECT
  trip_id,
  vehicle_id,
  driver_id,
  scheduled_arrival,
  actual_arrival,
  (actual_arrival - scheduled_arrival) AS arrival_delay
FROM transportation.trips
WHERE
  status = 'Completed'
  AND actual_arrival IS NOT NULL
  AND actual_arrival > scheduled_arrival + INTERVAL '45 minutes';

[User] For those completed trips with significant arrival delays, provide a count of how many fall into different delay duration categories: '45-90 mins', '>90 mins'.

[Assistant]
SELECT
  CASE
    WHEN (actual_arrival - scheduled_arrival) > INTERVAL '45 minutes' AND (actual_arrival - scheduled_arrival) <= INTERVAL '90 minutes' THEN '45-90 mins'
    WHEN (actual_arrival - scheduled_arrival) > INTERVAL '90 minutes' THEN '>90 mins'
    ELSE 'Other Delays' -- Should not be reached based on previous filter, but good practice
  END AS delay_category,
  COUNT(*)
FROM transportation.trips
WHERE
  status = 'Completed'
  AND actual_arrival IS NOT NULL
  AND actual_arrival > scheduled_arrival + INTERVAL '45 minutes'
GROUP BY
  delay_category;

[User] List consecutive fueling events for each vehicle where the refill quantity increased compared to the previous event. Include vehicle_id, previous timestamp and quantity, current timestamp and quantity.

[Assistant]
SELECT
  prev.vehicle_id,
  prev.log_timestamp AS previous_time,
  prev.quantity AS previous_quantity,
  curr.log_timestamp AS current_time,
  curr.quantity AS current_quantity
FROM (
  SELECT *, ROW_NUMBER() OVER (PARTITION BY vehicle_id ORDER BY log_timestamp) AS rn
  FROM transportation.fuel_logs
) prev
JOIN (
  SELECT *, ROW_NUMBER() OVER (PARTITION BY vehicle_id ORDER BY log_timestamp) AS rn
  FROM transportation.fuel_logs
) curr
  ON prev.vehicle_id = curr.vehicle_id
  AND curr.rn = prev.rn + 1
WHERE curr.quantity > prev.quantity;

[User] List the first and last names of clients whose client_id matches a lawyer_id in the time_entries table, along with the corresponding entry_id.

[Assistant] SELECT c.first_name, c.last_name, te.entry_id FROM legal_services.clients c JOIN legal_services.time_entries te ON c.client_id = te.lawyer_id;

[User] List each staff member who delivered orders, along with the number of orders they delivered.

[Assistant] SELECT staff_id_delivered, COUNT(order_id) AS delivered_orders FROM hospitality_technology.service_orders WHERE staff_id_delivered IS NOT NULL GROUP BY staff_id_delivered;

[User] Only show staff who delivered more than 10 orders.

[Assistant] SELECT staff_id_delivered, COUNT(order_id) AS delivered_orders FROM hospitality_technology.service_orders WHERE staff_id_delivered IS NOT NULL GROUP BY staff_id_delivered HAVING COUNT(order_id) > 10;


System:
You are an expert in writing database language. You can write a corresponding database language query to answer the user's question based on the table structure described by the table creation statement. ##Table Structure
CREATE TABLE legal_services.cases (
    case_id character varying(64) NOT NULL,  -- unique identifier for the case/matter
    case_number character varying(100) UNIQUE, -- official case number (court or internal)
    case_name text NOT NULL, -- descriptive name or title for the case
    client_id character varying(64) NOT NULL, -- FK to clients table
    lead_lawyer_id character varying(64) NOT NULL, -- FK to lawyers table (primary lawyer responsible)
    case_type character varying(100) NOT NULL, -- e.g., Litigation, Corporate, Family Law, IP
    status character varying(50) NOT NULL, -- e.g., Open, Closed, Pending, On Hold, Appealed
    date_opened timestamp NOT NULL, -- date the case was formally opened
    date_closed timestamp, -- date the case was closed (nullable)
    description text, -- detailed description of the case
    court_jurisdiction character varying(128), -- court or jurisdiction if applicable
    PRIMARY KEY (case_id)
)
CREATE TABLE legal_services.documents ( document_id.text, case_id.text, document_name.text, document_type.text, storage_path.text, uploaded_by_lawyer_id.text, upload_timestamp.timestamp, version.integer, description.text )
##Table Structure
CREATE TABLE legal_services.clients ( client_id text, first_name text, last_name text, company_name text, email text, phone text, address text, date_registered timestamp, status text )
CREATE TABLE legal_services.law_firms ( firm_id text, firm_name text, address text, phone text, website text, founded_date date, managing_partner_id text )
CREATE TABLE legal_services.cases ( case_id text, case_number text, case_name text, client_id text, lead_lawyer_id text, case_type text, status text, date_opened timestamp, date_closed timestamp, description text, court_jurisdiction text )
CREATE TABLE legal_services.invoices ( invoice_id text, invoice_number text, client_id text, case_id text, issue_date date, due_date date, total_amount numeric, amount_paid numeric, status text, payment_date timestamp, notes text, created_at timestamp )
##Table Structure
CREATE TABLE transportation.vehicles ( vehicle_id character varying(64) NOT NULL, license_plate character varying(32) NOT NULL UNIQUE, vin character varying(17) UNIQUE, make character varying(64) NOT NULL, model character varying(64) NOT NULL, year integer NOT NULL, type character varying(32) NOT NULL, capacity integer, fuel_type character varying(32) NOT NULL, status character varying(32) NOT NULL, depot_id character varying(64), acquisition_date date, PRIMARY KEY (vehicle_id) )
CREATE TABLE transportation.drivers ( driver_id character varying(64) NOT NULL, employee_id character varying(64) NOT NULL UNIQUE, first_name character varying(128) NOT NULL, last_name character varying(128) NOT NULL, license_number character varying(64) NOT NULL UNIQUE, license_expiry_date date NOT NULL, contact_number character varying(32), email character varying(128) UNIQUE, hire_date date NOT NULL, status character varying(32) NOT NULL, PRIMARY KEY (driver_id) )
CREATE TABLE transportation.trips ( trip_id character varying(64) NOT NULL, route_id character varying(64), vehicle_id character varying(64) NOT NULL, driver_id character varying(64) NOT NULL, scheduled_departure timestamp with time zone NOT NULL, actual_departure timestamp with time zone, scheduled_arrival timestamp with time zone NOT NULL, actual_arrival timestamp with time zone, origin_location_id character varying(64) NOT NULL, destination_location_id character varying(64) NOT NULL, status character varying(32) NOT NULL, passenger_count integer, cargo_manifest_id character varying(64), PRIMARY KEY (trip_id) )
CREATE TABLE transportation.locations ( location_id character varying(64) NOT NULL, name character varying(255) NOT NULL, type character varying(64) NOT NULL, address_line1 character varying(255), city character varying(128), state_province character varying(128), postal_code character varying(32), country character varying(64) NOT NULL, latitude numeric(9, 6), longitude numeric(9, 6), timezone character varying(64), PRIMARY KEY (location_id) )
CREATE TABLE transportation.maintenance_logs ( log_id character varying(64) NOT NULL, vehicle_id character varying(64) NOT NULL, service_date date NOT NULL, odometer_reading integer, service_type character varying(128) NOT NULL, description text NOT NULL, cost numeric(10, 2), mechanic_name character varying(128), next_service_due_date date, PRIMARY KEY (log_id) )
CREATE TABLE transportation.passengers ( passenger_id character varying(64) NOT NULL, first_name character varying(128) NOT NULL, last_name character varying(128) NOT NULL, email character varying(128) UNIQUE, phone_number character varying(32) UNIQUE, date_of_birth date, loyalty_program_id character varying(64), created_at timestamp with time zone NOT NULL, PRIMARY KEY (passenger_id) )
##Table Structure
CREATE TABLE transportation.maintenance_logs (
    log_id character varying(64) NOT NULL,  -- unique identifier for the maintenance record
    vehicle_id character varying(64) NOT NULL, -- identifier of the vehicle serviced
    service_date date NOT NULL, -- date the service was performed
    odometer_reading integer, -- vehicle mileage at time of service
    service_type character varying(128) NOT NULL, -- type of service (e.g., Oil Change, Tire Rotation, Engine Repair)
    description text NOT NULL, -- detailed description of work done
    cost numeric(10, 2), -- cost of the service
    mechanic_name character varying(128), -- name or ID of the mechanic/shop
    next_service_due_date date, -- recommended date for next service
    PRIMARY KEY (log_id)
)
##Table Structure
CREATE TABLE hospitality_technology.room_types ( room_type_id text PRIMARY KEY, property_id text, type_name text, description text, base_rate numeric, max_occupancy int, bed_type text, area_sqft numeric, amenities text )
##Table Structure
CREATE TABLE insurance.customers ( customer_id.text, first_name.text, last_name.text, date_of_birth.date, ssn_hash.text, address_line1.text, address_line2.text, city.text, state.text, zip_code.text, country.text, phone_number.text, email.text, created_at.timestamp, updated_at.timestamp, status.text )

[User] List all documents which have a version greater than 2, along with the case number and name.

[Assistant]
SELECT d.document_id, d.document_name, d.version, c.case_number, c.case_name
FROM legal_services.documents d
JOIN legal_services.cases c ON d.case_id = c.case_id
WHERE d.version > 2;

[User] Show all cases that are currently open and have a client whose status is prospect. Include the case_number, the case_name, and the client's full name.

[Assistant]
SELECT cs.case_number, cs.case_name, cl.first_name || ' ' || cl.last_name AS client_full_name
FROM legal_services.cases cs
JOIN legal_services.clients cl ON cs.client_id = cl.client_id
WHERE cs.status = 'Open' AND cl.status = 'prospect';

[User] List all trips including the name of the origin location and the name of the destination location.

[Assistant] SELECT t.trip_id, origin.name AS origin_location_name, destination.name AS destination_location_name FROM transportation.trips t JOIN transportation.locations origin ON t.origin_location_id = origin.location_id JOIN transportation.locations destination ON t.destination_location_id = destination.location_id;

[User] Show me all maintenance logs for 'Engine Repair' service type where the cost is greater than 400, including the vehicle ID, service date, cost, and mechanic name.

[Assistant] SELECT vehicle_id, service_date, cost, mechanic_name FROM transportation.maintenance_logs WHERE service_type = 'Engine Repair' AND cost > 400;

[User] Which bed types are offered in each property and how many different room types are associated with each bed type?

[Assistant] SELECT property_id, bed_type, COUNT(DISTINCT room_type_id) AS room_type_count FROM hospitality_technology.room_types GROUP BY property_id, bed_type;

[User] Now, show only bed types that are available for at least 3 different room types within the same property.

[Assistant] SELECT property_id, bed_type, COUNT(DISTINCT room_type_id) AS room_type_count FROM hospitality_technology.room_types GROUP BY property_id, bed_type HAVING COUNT(DISTINCT room_type_id) >= 3;

[User] How many customers have a non-null phone number in your system?

[Assistant] SELECT COUNT(*) FROM insurance.customers WHERE phone_number IS NOT NULL;


System:
You are an expert in writing database language. You can write a corresponding database language query to answer the user's question based on the table structure described by the table creation statement. ##Table Structure
CREATE TABLE insurance.customers ( customer_id text, first_name text, last_name text, date_of_birth date, ssn_hash text, address_line1 text, address_line2 text, city text, state text, zip_code text, country text, phone_number text, email text, created_at timestamp, updated_at timestamp, status text )
CREATE TABLE insurance.claims (
    claim_id character varying(64) NOT NULL, -- unique identifier for the claim
    policy_id character varying(64) NOT NULL, -- identifier of the policy under which the claim is made (FK to policies)
    customer_id character varying(64) NOT NULL, -- identifier of the customer making the claim (FK to customers)
    incident_date timestamp NOT NULL, -- date and time of the incident leading to the claim
    reported_date timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, -- date the claim was reported
    description text NOT NULL, -- detailed description of the incident and claim
    estimated_loss numeric(15, 2), -- initial estimated cost of the loss
    status character varying(30) NOT NULL, -- e.g., Filed, Processing, Under Review, Approved, Denied, Settled
    settlement_amount numeric(15, 2), -- final amount paid out
    settlement_date date,
    claim_handler_id character varying(64), -- identifier for the employee handling the claim (FK to employees/adjusters)
    police_report_number character varying(100),
    PRIMARY KEY (claim_id)
)
CREATE TABLE insurance.insurance_products (
    product_id character varying(64) NOT NULL, -- unique identifier for the insurance product
    product_name character varying(150) NOT NULL, -- name of the insurance product (e.g., 'Comprehensive Auto Insurance')
    product_type character varying(50) NOT NULL, -- category like 'Auto', 'Home', 'Life', 'Health', 'Travel'
    description text, -- detailed description of the product
    base_premium numeric(10, 2) NOT NULL, -- starting premium before adjustments
    coverage_details text, -- details about what is covered (could be JSON or structured text)
    underwriting_rules text, -- rules used for assessing risk and eligibility
    is_active boolean NOT NULL DEFAULT true, -- whether the product is currently offered
    created_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP,
    updated_at timestamp,
    PRIMARY KEY (product_id)
)
CREATE TABLE insurance.claim_documents ( document_id character varying(64) NOT NULL, claim_id character varying(64) NOT NULL, document_type character varying(50) NOT NULL, file_name character varying(255) NOT NULL, file_path character varying(512) NOT NULL, file_size_bytes integer, mime_type character varying(100), uploaded_by character varying(64), uploaded_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, description text, PRIMARY KEY (document_id) )
##Table Structure
CREATE TABLE blockchain.wallets ( wallet_id.text, user_id.text, address_id.text, private_key.text )
CREATE TABLE blockchain.users ( user_id.text, username.text, email.text, password_hash.text )
##Table Structure
CREATE TABLE trading_platform.orders ( order_id text PRIMARY KEY, user_id text, wallet_id text, asset_id text, order_type text, quantity numeric, price numeric, status text, created_at timestamp )
CREATE TABLE trading_platform.trades ( trade_id text PRIMARY KEY, order_id text, buyer_id text, seller_id text, asset_id text, quantity numeric, price numeric, traded_at timestamp )
CREATE TABLE trading_platform.utxos ( utxo_id text PRIMARY KEY, transaction_id text, output_index int, address text, amount numeric, spent boolean )
CREATE TABLE trading_platform.dapps ( dapp_id text PRIMARY KEY, name text, description text, url text )
CREATE TABLE trading_platform.peers ( peer_id text PRIMARY KEY, ip_address text, port int, last_seen timestamp )
CREATE TABLE trading_platform.metadata ( metadata_id text PRIMARY KEY, asset_id text, key text, value text )
CREATE TABLE trading_platform.kyc_audit ( kyc_audit_id text PRIMARY KEY, user_id text, status text, reviewed_at timestamp )
CREATE TABLE trading_platform.logs ( log_id text PRIMARY KEY, user_id text, action text, details text, logged_at timestamp )
##Table Structure
CREATE TABLE transportation.routes ( route_id text, route_number text, description text, origin_location_id text, destination_location_id text, distance_km numeric, estimated_duration_minutes integer, type text )
##Table Structure
CREATE TABLE insurance.premium_payments ( payment_id character varying(64) NOT NULL, policy_id character varying(64) NOT NULL, customer_id character varying(64) NOT NULL, payment_date timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, amount_paid numeric(12, 2) NOT NULL, payment_method character varying(50), transaction_reference character varying(128) UNIQUE, due_date date, payment_period_start date, payment_period_end date, status character varying(30) NOT NULL DEFAULT 'Completed', PRIMARY KEY (payment_id) )
##Table Structure
CREATE TABLE web3.events ( event_id character varying(64) NOT NULL, contract_id character varying(64) NOT NULL, event_name character varying(128) NOT NULL, data text NOT NULL, emitted_at timestamp NOT NULL, transaction_id character varying(64) NOT NULL, log_index integer NOT NULL, PRIMARY KEY (event_id) )
##Table Structure
CREATE TABLE government_services.notifications ( notification_id text, citizen_id text, application_id text, message_subject text, message_body text, channel text, sent_at timestamp, status text, related_entity_type text, related_entity_id text )
##Table Structure
CREATE TABLE government_services.documents ( document_id text, application_id text, citizen_id text, document_type text, file_reference text, upload_timestamp timestamp, expiry_date date, verification_status text, verified_by_employee_id text, verification_timestamp timestamp )

[User] Show the total number of customers in each state.

[Assistant]
SELECT
  state,
  COUNT(customer_id)
FROM insurance.customers
GROUP BY
  state;

[User] List all users whose password hash contains the substring 'abc'.

[Assistant] SELECT user_id, username, password_hash FROM blockchain.users WHERE password_hash LIKE '%abc%';

[User] Also include their email address.

[Assistant] SELECT user_id, username, password_hash, email FROM blockchain.users WHERE password_hash LIKE '%abc%';

[User] Filter to only show users whose username does *not* contain 'test'.

[Assistant] SELECT user_id, username, password_hash, email FROM blockchain.users WHERE password_hash LIKE '%abc%' AND username NOT LIKE '%test%';

[User] Show a list of all DApps together with the total number of unique assets linked to each via the metadata table.

[Assistant]
SELECT d.dapp_id, d.name, d.url, COUNT(DISTINCT m.asset_id) AS unique_asset_count
FROM trading_platform.dapps d
LEFT JOIN trading_platform.metadata m ON m.asset_id IS NOT NULL
GROUP BY d.dapp_id, d.name, d.url;

[User] Find all pairs of different routes where the estimated duration in minutes is identical. For each pair, show both route IDs, their route numbers, and the shared duration.

[Assistant] SELECT r1.route_id AS route1_id, r1.route_number AS route1_number, r2.route_id AS route2_id, r2.route_number AS route2_number, r1.estimated_duration_minutes FROM transportation.routes r1 JOIN transportation.routes r2 ON r1.estimated_duration_minutes = r2.estimated_duration_minutes AND r1.route_id < r2.route_id;

[User] For each payment status, how many payments were made and what was the total amount paid? Order the results by the total amount paid in descending order.

[Assistant] SELECT status, COUNT(*) AS payment_count, SUM(amount_paid) AS total_amount FROM insurance.premium_payments GROUP BY status ORDER BY total_amount DESC;

[User] Can you find the contract that has emitted the most events, and show its contract ID along with the total number of events emitted?

[Assistant] SELECT contract_id, COUNT(*) AS total_events FROM web3.events GROUP BY contract_id ORDER BY total_events DESC LIMIT 1;

[User] List all notifications sent through the 'Email' channel, showing all columns.

[Assistant] SELECT notification_id, citizen_id, application_id, message_subject, message_body, channel, sent_at, status, related_entity_type, related_entity_id FROM government_services.notifications WHERE channel = 'Email';

[User] List the full names of employees who have verified 'Proof of Identity' documents.

[Assistant] SELECT DISTINCT T1.first_name, T1.last_name FROM government_services.employees AS T1 JOIN government_services.documents AS T2 ON T1.employee_id = T2.verified_by_employee_id WHERE T2.document_type = 'Proof of Identity';


System:
You are an expert in writing database language. You can write a corresponding database language query to answer the user's question based on the table structure described by the table creation statement. ##Table Structure
CREATE TABLE transportation.vehicles (
    vehicle_id character varying(64) NOT NULL,  -- unique identifier for the vehicle
    license_plate character varying(32) NOT NULL UNIQUE, -- vehicle license plate
    vin character varying(17) UNIQUE, -- vehicle identification number
    make character varying(64) NOT NULL, -- manufacturer of the vehicle
    model character varying(64) NOT NULL, -- model of the vehicle
    year integer NOT NULL, -- manufacturing year
    type character varying(32) NOT NULL, -- type of vehicle (e.g., Bus, Train, Truck, Car, Van)
    capacity integer, -- passenger or cargo capacity
    fuel_type character varying(32) NOT NULL, -- e.g., Diesel, Gasoline, Electric, Hydrogen
    status character varying(32) NOT NULL, -- e.g., Active, Maintenance, Decommissioned
    depot_id character varying(64), -- identifier of the home depot/base
    acquisition_date date, -- date the vehicle was acquired
    PRIMARY KEY (vehicle_id)
)
CREATE TABLE transportation.routes ( route_id.text, route_number.text, description.text, origin_location_id.text, destination_location_id.text, distance_km.numeric, estimated_duration_minutes.integer, type.text )
CREATE TABLE transportation.trips ( trip_id text PRIMARY KEY, route_id text, vehicle_id text, driver_id text, scheduled_departure timestamp, actual_departure timestamp, scheduled_arrival timestamp, actual_arrival timestamp, origin_location_id text, destination_location_id text, status text, passenger_count int, cargo_manifest_id text )
CREATE TABLE transportation.maintenance_logs ( log_id text PRIMARY KEY, vehicle_id text, service_date date, odometer_reading int, service_type text, description text, cost numeric, mechanic_name text, next_service_due_date date )
##Table Structure
CREATE TABLE token_dexpool_info ( pair_address character varying(512) NOT NULL, token_name character varying(100) NOT NULL, token_symbol character varying(100) NOT NULL, chain text, price double precision, price_change_percentage_1h double precision, price_change_percentage_6h double precision, price_change_percentage_24h double precision, makers_24h double precision, volume_24h double precision, liquidity double precision, market_cap double precision, trend_rank bigint )
##Table Structure
CREATE TABLE insurance.policies ( policy_id text PRIMARY KEY, customer_id text, product_id text, agent_id text, policy_number text, start_date date, end_date date, premium_amount numeric, coverage_limit numeric, deductible numeric, status text, issued_at timestamp, cancellation_date date, cancellation_reason text )
##Table Structure
CREATE TABLE trading_platform.wallets ( wallet_id.text, user_id.text, address.text, private_key.text, created_at.timestamp )
##Table Structure
CREATE TABLE transportation.drivers ( driver_id text PRIMARY KEY, employee_id text, first_name text, last_name text, license_number text, license_expiry_date date, contact_number text, email text, hire_date date, status text )
CREATE TABLE transportation.routes ( route_id text, route_number text, description text, origin_location_id text, destination_location_id text, distance_km numeric, estimated_duration_minutes integer, type text )
CREATE TABLE transportation.trips ( trip_id.text, route_id.text, vehicle_id.text, driver_id.text, scheduled_departure.timestamp, actual_departure.timestamp, scheduled_arrival.timestamp, actual_arrival.timestamp, origin_location_id.text, destination_location_id.text, status.text, passenger_count.integer, cargo_manifest_id.text )
CREATE TABLE transportation.locations ( location_id text PRIMARY KEY, name text, type text, address_line1 text, city text, state_province text, postal_code text, country text, latitude numeric, longitude numeric, timezone text )
CREATE TABLE transportation.maintenance_logs ( log_id character varying(64) NOT NULL, vehicle_id character varying(64) NOT NULL, service_date date NOT NULL, odometer_reading integer, service_type character varying(128) NOT NULL, description text NOT NULL, cost numeric(10, 2), mechanic_name character varying(128), next_service_due_date date, PRIMARY KEY (log_id) )
CREATE TABLE transportation.passengers ( passenger_id.text, first_name.text, last_name.text, email.text, phone_number.text, date_of_birth.date, loyalty_program_id.text, created_at.timestamp )

[User] For each route, show its route number, distance in kilometers, and the total number of trips that have used that route.

[Assistant]
SELECT r.route_number, r.distance_km, COUNT(t.trip_id) AS trip_count
FROM transportation.routes r
LEFT JOIN transportation.trips t ON r.route_id = t.route_id
GROUP BY r.route_number, r.distance_km;

[User] Show me the top 5 tokens by 24-hour trading volume on the Ethereum chain, along with their price and 24-hour price change percentage.

[Assistant] SELECT token_name, token_symbol, price, price_change_percentage_24h, volume_24h FROM token_dexpool_info WHERE chain = 'Ethereum' ORDER BY volume_24h DESC LIMIT 5;

[User] Can you also include the market cap and liquidity for these tokens?

[Assistant] SELECT token_name, token_symbol, price, price_change_percentage_24h, volume_24h, market_cap, liquidity FROM token_dexpool_info WHERE chain = 'Ethereum' ORDER BY volume_24h DESC LIMIT 5;

[User] Show me all policies that expired in the last 60 days, along with their product IDs and premium amounts.

[Assistant] SELECT policy_id, product_id, premium_amount FROM insurance.policies WHERE status = 'expired' AND end_date >= CURRENT_DATE - INTERVAL '60 days' AND end_date <= CURRENT_DATE;

[User] Now include only policies that had a deductible of $1000 or more.

[Assistant] SELECT policy_id, product_id, premium_amount, deductible FROM insurance.policies WHERE status = 'expired' AND end_date >= CURRENT_DATE - INTERVAL '60 days' AND end_date <= CURRENT_DATE AND deductible >= 1000;

[User] I also want to see the count of such expired policies per product ID.

[Assistant] SELECT product_id, COUNT(*) as policy_count FROM insurance.policies WHERE status = 'expired' AND end_date >= CURRENT_DATE - INTERVAL '60 days' AND end_date <= CURRENT_DATE AND deductible >= 1000 GROUP BY product_id ORDER BY policy_count DESC;

[User] Finally, show me the average premium amount for these expired high-deductible policies grouped by product ID.

[Assistant] SELECT product_id, AVG(premium_amount) as avg_premium FROM insurance.policies WHERE status = 'expired' AND end_date >= CURRENT_DATE - INTERVAL '60 days' AND end_date <= CURRENT_DATE AND deductible >= 1000 GROUP BY product_id ORDER BY avg_premium DESC;

[User] List pairs of wallets created on the same day but belonging to different users. Show the wallet IDs, user IDs, and creation dates for both wallets in each pair.

[Assistant] SELECT w1.wallet_id AS wallet1_id, w1.user_id AS user1_id, w1.created_at AS wallet1_created_at, w2.wallet_id AS wallet2_id, w2.user_id AS user2_id, w2.created_at AS wallet2_created_at FROM wallets w1 JOIN wallets w2 ON DATE(w1.created_at) = DATE(w2.created_at) AND w1.user_id != w2.user_id AND w1.wallet_id < w2.wallet_id;

[User] Filter the previous results to only include pairs where both wallet addresses start with '0x'.

[Assistant] SELECT w1.wallet_id AS wallet1_id, w1.user_id AS user1_id, w1.created_at AS wallet1_created_at, w2.wallet_id AS wallet2_id, w2.user_id AS user2_id, w2.created_at AS wallet2_created_at FROM wallets w1 JOIN wallets w2 ON DATE(w1.created_at) = DATE(w2.created_at) AND w1.user_id != w2.user_id AND w1.wallet_id < w2.wallet_id WHERE w1.address LIKE '0x%' AND w2.address LIKE '0x%';

[User] Compute the average and maximum cost of maintenance for each service_type in the maintenance_logs table.

[Assistant]
SELECT service_type,
       AVG(cost) AS avg_cost,
       MAX(cost) AS max_cost
FROM transportation.maintenance_logs
GROUP BY service_type;

[User] Now restrict the result to only those service_type entries where avg_cost > 200.

[Assistant]
SELECT service_type,
       AVG(cost) AS avg_cost,
       MAX(cost) AS max_cost
FROM transportation.maintenance_logs
GROUP BY service_type
HAVING AVG(cost) > 200;