Triple

T22153585
Position Surface form Disambiguated ID Type / Status
Subject Open Window, Nice E547474 entity
Predicate locationDepicted P3858 FINISHED
Object Nice, France NE NERFINISHED

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: Nice, France | Statement: [Open Window, Nice, locationDepicted, Nice, France]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nice, France
Context triple: [Open Window, Nice, locationDepicted, Nice, France]
  • A. Nice, France chosen
    Nice, France is a major Mediterranean coastal city on the French Riviera known for its picturesque Promenade des Anglais, vibrant arts scene, and historic old town.
  • B. Noailles, France
    Noailles, France is a small commune in northern France known for its historical ties to the noble de Noailles family.
  • C. Roymont, France
    Roymont, France is a locality in France historically noted as the place where Joan II, Countess of Burgundy, died.
  • D. Douai, France
    Douai, France is a historic town in northern France known for its medieval belfry, legal and university traditions, and role as a regional administrative center.
  • E. Vertain, France
    Vertain, France is a small commune in the Nord department of northern France, known among cycling fans as the burial place of legendary French cyclist Jean Stablinski.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e3b52088190ad5df386d01eb2fb completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f129f6d5b88190badee2e515a3b633 completed April 28, 2026, 9:43 p.m.
Created at: April 16, 2026, 8:33 p.m.