Triple

T7867882
Position Surface form Disambiguated ID Type / Status
Subject Collégiale Saint-Laurent de Joinville E182662 entity
Predicate locatedIn P40 FINISHED
Object Haute-Marne E131592 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: Haute-Marne | Statement: [Collégiale Saint-Laurent de Joinville, locatedIn, Haute-Marne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Haute-Marne
Context triple: [Collégiale Saint-Laurent de Joinville, locatedIn, Haute-Marne]
  • A. Haute-Marne chosen
    Haute-Marne is a rural department in northeastern France known for its forests, rivers, and historic towns such as Chaumont and Langres.
  • B. Seine-et-Marne
    Seine-et-Marne is a largely rural department in north-central France east of Paris, known for its historic towns, agricultural landscapes, and attractions such as the Château de Fontainebleau and Disneyland Paris.
  • C. Haute-Saône
    Haute-Saône is a rural department in the Bourgogne-Franche-Comté region of eastern France, known for its forests, rivers, and historic villages.
  • D. Meurthe-et-Moselle
    Meurthe-et-Moselle is a department in northeastern France known for its capital Nancy, rich industrial history, and Art Nouveau architectural heritage.
  • E. Seine-et-Oise
    Seine-et-Oise was a former department of France surrounding Paris, abolished in 1968 and divided into several new departments including Yvelines.
  • 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_69ca82894d9081908a832bfce71a4714 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3847c7fc819098e32b6548943da7 completed March 31, 2026, 2:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69cbdf6fb33881908cf7bd68915aa6b4 completed March 31, 2026, 2:51 p.m.
Created at: March 30, 2026, 4:55 p.m.