Triple

T2598881
Position Surface form Disambiguated ID Type / Status
Subject Balenciaga E58295 entity
Predicate hasFlagshipStoreIn P15696 FINISHED
Object Paris E568 NE FINISHED

How this triple was built (3 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Paris | Statement: [Balenciaga, hasFlagshipStoreIn, Paris]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paris
Context triple: [Balenciaga, hasFlagshipStoreIn, Paris]
  • A. Paris
    Paris is a prince of Troy in Greek mythology, best known for judging the beauty contest of the goddesses and for abducting Helen, which sparked the Trojan War.
  • B. Paris chosen
    Paris is the capital and largest city of France, renowned for its historic architecture, art, fashion, and cultural influence worldwide.
  • C. Lyon
    Lyon is a major city in east-central France known for its historical and architectural landmarks, gastronomy, and role as a key economic and cultural center.
  • D. Palaiseau
    Palaiseau is a suburban commune in the southern outskirts of Paris, France, known for hosting major scientific and engineering institutions.
  • E. Boulogne-Billancourt
    Boulogne-Billancourt is a densely populated suburban city just southwest of central Paris, known as a major economic and media hub in the Île-de-France region.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasFlagshipStoreIn
Context triple: [Balenciaga, hasFlagshipStoreIn, Paris]
  • A. hasRetailPresenceIn
    Indicates that an entity conducts retail operations or maintains a retail outlet, store, or sales presence within a specified location.
  • B. hasRetailBoutiquesIn chosen
    Indicates that an entity operates or maintains retail boutiques located within a specified place or region.
  • C. hasShopsOn
    Indicates that one entity (typically a street, area, or building) contains or is lined with shops located on or along it.
  • D. hasShop
    Indicates that one entity owns, operates, or is associated with a shop or retail establishment.
  • E. reportedlyStores
    Indicates that an entity is said or believed, based on reports or claims, to store or hold another entity, without confirming that this storage actually occurs.
  • F. None of above.

Provenance (4 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69ab4ac14040819098b13f4a27d5c8ff completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abd4563b8c8190934616651e93654c completed March 7, 2026, 7:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69af906f488481909e5e45d8405022b5 completed March 10, 2026, 3:30 a.m.
PD Predicate disambiguation batch_69abd0d4e8648190b612eb09aa085451 completed March 7, 2026, 7:16 a.m.
Created at: March 6, 2026, 9:49 p.m.