Triple

T11013952
Position Surface form Disambiguated ID Type / Status
Subject Lac du Der-Chantecoq E260314 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: [Lac du Der-Chantecoq, locatedIn, Haute-Marne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Haute-Marne
Context triple: [Lac du Der-Chantecoq, 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_69d6aa9687448190b28d353b1b6a610e completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d797a49f648190a5144625d09dec6f completed April 9, 2026, 12:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69e374c238ac81908e0a5eff958d6545 completed April 18, 2026, 12:10 p.m.
Created at: April 8, 2026, 9:25 p.m.