Triple

T16627357
Position Surface form Disambiguated ID Type / Status
Subject Guillaume Coustou E403983 entity
Predicate workLocation P7 FINISHED
Object Versailles E9321 NE FINISHED

How this triple was built (2 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: Versailles | Statement: [Guillaume Coustou, workLocation, Versailles]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Versailles
Context triple: [Guillaume Coustou, workLocation, Versailles]
  • A. Versailles chosen
    Versailles is a historic French city best known for the opulent Palace of Versailles, a former royal residence and a symbol of absolute monarchy and French cultural grandeur.
  • B. Versailles
    "Versailles" is a historical drama television series centered on the reign of France's King Louis XIV and the political intrigue surrounding the construction and life at the Palace of Versailles.
  • C. Versailles
    Versailles is a small borough in Allegheny County, Pennsylvania, situated along the Youghiogheny River in the Pittsburgh metropolitan area.
  • D. Château de Versailles
    The Château de Versailles is a grand former royal palace near Paris, renowned for its opulent architecture, expansive gardens, and central role in French history and culture.
  • E. Párizsi udvar
    Párizsi udvar is an ornate early-20th-century commercial and residential building in central Budapest, famed for its eclectic, neo-Gothic and Art Nouveau architecture and lavish interior arcade.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d883897eb481909eaaa088ba9918d9 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e378e2683481908c9a5ed895a09a6e completed April 18, 2026, 12:28 p.m.
NED1 Entity disambiguation (via context triple) batch_6a007dba91bc819090a78ac4c0c01fc8 completed May 10, 2026, 12:44 p.m.
Created at: April 10, 2026, 5:17 a.m.