scripts/gen_ies_ground.py

"""Correct-by-construction IES4 training data.
Builds valid IES4 graphs with telicent-ies-tool across 12 patterns, double-validates
each (telicent SHACL + our term-membership validator), and emits
{pattern, facts, turtle} records. A deterministic natural-language 'facts' string is
attached; a later step paraphrases it with the local Qwen for linguistic diversity.
Run under .venv311 (telicent needs py>=3.10)."""
import sys, json, pathlib, random, argparse
sys.path.insert(0, str(pathlib.Path(__file__).parent))
from ies_tool.ies_tool import (IESTool, Person, Organisation, Event, Location,
                               Device, Asset, Communication, PartyInCommunication)
from iesval import validate_turtle

random.seed(101)
ROOT = pathlib.Path("/Users/fabio/projects/qwen-ies-ft")

GIVEN = ["Fred","Alice","Barry","Priya","Vladimir","Chen","Amara","Sofia","Liam","Yusuf",
         "Grace","Diego","Nadia","Tom","Ivy","Omar","Hannah","Kofi","Elena","Sam"]
SUR = ["Smith","Okafor","Patel","Ivanov","Wang","Rossi","Khan","Nguyen","Brown","Silva",
       "Adebayo","Muller","Kowalski","Andersson","Costa","Haddad","Murphy","Reyes"]
ORGS = ["Acme Logistics Ltd","Northgate Shipping","Meridian Bank","Halcyon Devices",
        "Blue Harbour Freight","Sterling Manufacturing","Corvus Security","Pine Valley Clinic",
        "Redwood Analytics","Orion Telecom","Harbourline Ferries","Vertex Engineering"]
PLACES = ["Port of Dover","Heathrow Terminal 4","Manchester Depot","University Hospital",
          "Felixstowe Docks","Kings Cross Station","Birmingham Warehouse","Gatwick Cargo",
          "Southampton Container Port","Leeds Distribution Centre","Bristol Harbour"]
CITIES = ["London","Manchester","Birmingham","Glasgow","Cardiff","Belfast","Leeds","Dover"]
DEVICES = ["Nokia handset","Samsung Galaxy phone","Toyota Hilux van","DAF articulated lorry",
           "Dell laptop","Yamaha outboard motor","forklift truck","Land Rover Defender"]
POSTS = ["Warehouse Supervisor","Chief Engineer","Compliance Officer","Ship's Master",
         "Security Analyst","Ward Nurse","Logistics Coordinator","Border Officer"]
UNITS = [("kilogram","kg"),("metre","m"),("year","yr"),("centimetre","cm")]

def yr(a=1970,b=2005): return random.randint(a,b)
def date(y=None):
    y = y or yr(2010,2024)
    return f"{y}-{random.randint(1,12):02d}-{random.randint(1,28):02d}"
def dt(): return date(yr(2018,2024))+f"T{random.randint(6,20):02d}:00:00"

def new():
    t = IESTool(); t.default_data_namespace = "http://data.gov.uk/testdata#"; return t

# ---- each template returns (facts:str, turtle:str) using a fresh tool ----
def t_employment():
    t=new(); g=random.choice(GIVEN); s=random.choice(SUR); org=random.choice(ORGS)
    o=Organisation(tool=t, name=org)
    dob=date(yr(1960,1998))
    p=Person(tool=t, given_name=g, surname=s, date_of_birth=dob)
    start=date(yr(2012,2020)); p.works_for(o, start=start)
    facts=f"{g} {s}, born {dob}, has worked for {org} since {start}."
    return facts, t.get_rdf(rdf_format="turtle")["triples"]

def t_employment_ended():
    t=new(); g=random.choice(GIVEN); s=random.choice(SUR); org=random.choice(ORGS)
    o=Organisation(tool=t, name=org)
    p=Person(tool=t, given_name=g, surname=s)
    a=yr(2008,2016); b=yr(2017,2023)
    p.works_for(o, start=date(a), end=date(b))
    facts=f"{g} {s} worked for {org} from {a} until {b}, then left."
    return facts, t.get_rdf(rdf_format="turtle")["triples"]

def t_birth_death():
    t=new(); g=random.choice(GIVEN); s=random.choice(SUR)
    bp=Location(tool=t); bp.add_name(random.choice(CITIES))
    p=Person(tool=t, given_name=g, surname=s)
    p.add_birth(date_of_birth=date(yr(1930,1960)), place_of_birth=bp)
    if random.random()<0.6:
        dp=Location(tool=t); dp.add_name(random.choice(CITIES))
        p.add_death(date_of_death=date(yr(2000,2023)), place_of_death=dp)
        facts=f"{g} {s} was born in one city and later died in another."
    else:
        facts=f"{g} {s} was born in a UK city."
    return facts, t.get_rdf(rdf_format="turtle")["triples"]

def t_event_participation():
    t=new(); loc=Location(tool=t); loc.add_name(random.choice(PLACES))
    ev=Event(tool=t, start=dt(), end=dt()); ev.add_name(random.choice(
        ["team meeting","container inspection","cargo handover","security briefing","site visit"]))
    ev.in_location(loc)
    people=[]
    for _ in range(random.randint(2,4)):
        p=Person(tool=t, given_name=random.choice(GIVEN), surname=random.choice(SUR))
        ev.add_participant(p); people.append(p)
    facts=(f"{len(people)} people took part in an event at {loc}, which had a start and end time.")
    return facts, t.get_rdf(rdf_format="turtle")["triples"]

def t_identifier():
    t=new(); g=random.choice(GIVEN); s=random.choice(SUR)
    p=Person(tool=t, given_name=g, surname=s)
    num=f"{random.randint(10,99)}{random.choice('ABCDEFGH')}{random.randint(1000,9999)}"
    p.add_identifier(num, id_class="http://ies.data.gov.uk/ontology/ies4#NationalIdentityNumber")
    facts=f"{g} {s} is identified by the national identity number {num}."
    return facts, t.get_rdf(rdf_format="turtle")["triples"]

def t_ownership():
    t=new(); g=random.choice(GIVEN); s=random.choice(SUR); d=random.choice(DEVICES)
    p=Person(tool=t, given_name=g, surname=s)
    dev=Device(tool=t); dev.add_name(d)
    p.owns(dev, start=date(yr(2015,2022)))
    facts=f"{g} {s} owns a {d}, acquired at a known date."
    return facts, t.get_rdf(rdf_format="turtle")["triples"]

def t_post_holding():
    t=new(); g=random.choice(GIVEN); s=random.choice(SUR); org=random.choice(ORGS); post=random.choice(POSTS)
    o=Organisation(tool=t, name=org)
    pp=o.create_post(name=post, start=date(yr(2016,2021)))
    p=Person(tool=t, given_name=g, surname=s)
    p.in_post(pp, start=date(yr(2016,2021)))
    facts=f"{g} {s} holds the post of {post} at {org}."
    return facts, t.get_rdf(rdf_format="turtle")["triples"]

def t_location_state():
    t=new(); g=random.choice(GIVEN); s=random.choice(SUR)
    loc=Location(tool=t); loc.add_name(random.choice(PLACES))
    p=Person(tool=t, given_name=g, surname=s)
    p.create_state(start=dt(), end=dt(), in_location=loc)
    facts=f"{g} {s} was present at {loc} for a bounded period of time."
    return facts, t.get_rdf(rdf_format="turtle")["triples"]

def t_access():
    t=new(); g=random.choice(GIVEN); s=random.choice(SUR); d=random.choice(DEVICES)
    p=Person(tool=t, given_name=g, surname=s)
    dev=Device(tool=t); dev.add_name(d)
    p.has_access_to(dev, start=date(yr(2019,2023)))
    facts=f"{g} {s} has access to a {d} from a given date."
    return facts, t.get_rdf(rdf_format="turtle")["triples"]

def t_org_owns_asset():
    t=new(); org=random.choice(ORGS); d=random.choice(DEVICES)
    o=Organisation(tool=t, name=org); a=Asset(tool=t); a.add_name(d)
    o.owns(a, start=date(yr(2010,2020)))
    facts=f"{org} owns a {d} as one of its assets."
    return facts, t.get_rdf(rdf_format="turtle")["triples"]

def t_possession():
    t=new(); g=random.choice(GIVEN); s=random.choice(SUR); d=random.choice(DEVICES)
    p=Person(tool=t, given_name=g, surname=s)
    dev=Device(tool=t); dev.add_name(d)
    p.in_possession_of(dev, start=dt())
    facts=f"{g} {s} was in possession of a {d} from a certain time."
    return facts, t.get_rdf(rdf_format="turtle")["triples"]

def t_communication():
    t=new(); g1,s1=random.choice(GIVEN),random.choice(SUR); g2,s2=random.choice(GIVEN),random.choice(SUR)
    p1=Person(tool=t, given_name=g1, surname=s1); p2=Person(tool=t, given_name=g2, surname=s2)
    d1=Device(tool=t); d1.add_name(random.choice(DEVICES)); d2=Device(tool=t); d2.add_name(random.choice(DEVICES))
    st=dt()
    comm=Communication(tool=t, start=st)
    pa=comm.create_party(); pa.add_person(p1); pa.add_device(d1)
    pb=comm.create_party(); pb.add_person(p2); pb.add_device(d2)
    facts=(f"{g1} {s1} and {g2} {s2} took part in a communication that began at {st}, "
           f"each using their own device.")
    return facts, t.get_rdf(rdf_format="turtle")["triples"]

def t_composite_case():
    # person + employment + attends event at location + possesses device
    t=new(); g,s=random.choice(GIVEN),random.choice(SUR); org=random.choice(ORGS)
    o=Organisation(tool=t, name=org)
    p=Person(tool=t, given_name=g, surname=s, date_of_birth=date(yr(1965,1995)))
    p.works_for(o, start=date(yr(2014,2020)))
    dev=Device(tool=t); dev.add_name(random.choice(DEVICES)); p.in_possession_of(dev, start=dt())
    loc=Location(tool=t); loc.add_name(random.choice(PLACES))
    ev=Event(tool=t, start=dt(), end=dt()); ev.add_name(random.choice(
        ["site inspection","handover meeting","security review"])); ev.in_location(loc)
    ev.add_participant(p)
    facts=(f"{g} {s} works for {org}, was in possession of a device, and attended an event "
           f"with a start and end time held at {loc}.")
    return facts, t.get_rdf(rdf_format="turtle")["triples"]

def t_composite_org():
    # organisation with post, post-holder, owned asset, and an event at a location
    t=new(); org=random.choice(ORGS); post=random.choice(POSTS); g,s=random.choice(GIVEN),random.choice(SUR)
    o=Organisation(tool=t, name=org)
    pp=o.create_post(name=post, start=date(yr(2015,2020)))
    p=Person(tool=t, given_name=g, surname=s); p.in_post(pp, start=date(yr(2016,2021)))
    a=Asset(tool=t); a.add_name(random.choice(DEVICES)); o.owns(a, start=date(yr(2012,2019)))
    loc=Location(tool=t); loc.add_name(random.choice(PLACES))
    ev=Event(tool=t, start=dt(), end=dt()); ev.add_name("audit visit"); ev.in_location(loc)
    ev.add_participant(p)
    facts=(f"{org} has the post of {post}, held by {g} {s}, owns an asset, and hosted an "
           f"audit visit at {loc} that {g} attended.")
    return facts, t.get_rdf(rdf_format="turtle")["triples"]

TEMPLATES = [t_employment, t_employment_ended, t_birth_death, t_event_participation,
             t_identifier, t_ownership, t_post_holding, t_location_state,
             t_access, t_org_owns_asset, t_possession,
             t_communication, t_composite_case, t_composite_org]

def main():
    ap=argparse.ArgumentParser(); ap.add_argument("--n", type=int, default=1200)
    args=ap.parse_args()
    out=(ROOT/"data"/"ground.jsonl").open("w")
    kept=0; fail=0; per={}
    for i in range(args.n):
        fn=TEMPLATES[i % len(TEMPLATES)]
        try:
            facts, ttl = fn()
        except Exception as e:
            fail+=1; continue
        ok, reason, n, _ = validate_turtle(ttl, min_triples=5)
        if ok:
            out.write(json.dumps({"pattern":fn.__name__, "facts":facts, "turtle":ttl})+"\n")
            kept+=1; per[fn.__name__]=per.get(fn.__name__,0)+1
        else:
            fail+=1
    out.close()
    print(f"ground pairs kept={kept} failed={fail}")
    for k in sorted(per): print(f"  {k}: {per[k]}")

if __name__=="__main__":
    main()