Triple

T14873204
Position Surface form Disambiguated ID Type / Status
Subject Louvre INV 253 E349801 entity
Predicate associatedWorkLocation P1527 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: [Louvre INV 253, associatedWorkLocation, Paris]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paris
Context triple: [Louvre INV 253, associatedWorkLocation, Paris]
  • A. Paris chosen
    Paris is the capital and largest city of France, renowned for its historic architecture, art, fashion, and cultural influence worldwide.
  • B. 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.
  • C. Paris
    Paris is a major Chilean department store and retail chain offering a wide range of apparel, home goods, and consumer products.
  • D. Paris
    Paris is a budget-oriented AMD Sempron processor core designed for entry-level desktop computing.
  • E. Paris
    Paris was an enslaved man held in bondage by George Washington at the President's House in Philadelphia during his presidency.
  • 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: associatedWorkLocation
Context triple: [Louvre INV 253, associatedWorkLocation, Paris]
  • A. locationOfWork chosen
    Indicates the place or site where an entity performs its work or carries out its professional activities.
  • B. locationInWork
    Indicates that one entity specifies the place or setting where another entity occurs, is situated, or takes place within a particular work (e.g., a scene’s location in a film or a chapter’s setting in a book).
  • C. residenceInWork
    Indicates that an entity’s place of residence is located within or at the same site as their place of work.
  • D. depictsWorkLocation
    Indicates that one entity visually represents the place where another entity performs its work or professional activities.
  • E. appliedToWorkCurrentLocation
    Indicates that an application was submitted for a job or position at the entity’s current work location.
  • 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_69d822ee4f408190b6ac3b2fa434f0df completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69ded5e2c94c8190a16f05ea81701fc1 completed April 15, 2026, 12:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe64f0d948819080cc759ca599503d completed May 8, 2026, 10:34 p.m.
PD Predicate disambiguation batch_69de8c1a2bcc81908f914e2e2ced65eb completed April 14, 2026, 6:48 p.m.
Created at: April 10, 2026, 1:55 a.m.