"""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()