Triple

T2122453
Position Surface form Disambiguated ID Type / Status
Subject Langres Plateau E43955 entity
Predicate sourceRegionOf P410 FINISHED
Object Aube E43606 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: Aube | Statement: [Langres Plateau, sourceRegionOf, Aube]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aube
Context triple: [Langres Plateau, sourceRegionOf, Aube]
  • A. Aube chosen
    Aube is a department in northeastern France known for its historic towns, Champagne vineyards, and rural landscapes.
  • B. Thiérache
    Thiérache is a rural, historically fortified region in northern France known for its bocage landscapes, brick churches, and traditional dairy production.
  • C. Val-d'Oise
    Val-d'Oise is a department in northern France that forms part of the Paris metropolitan region and includes both suburban areas and rural landscapes.
  • D. Oise
    Oise is a major river in northern France that flows through regions such as Picardy and Île-de-France before joining the Seine near Paris.
  • E. Dauphiné
    Dauphiné is a historical region in southeastern France, centered around Grenoble in the Alps, known for its role in French history and distinctive alpine culture.
  • 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_69a88717cfe48190b7ecdd68c824848a completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abbdc3a12081908e95ae870207367f completed March 7, 2026, 5:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69aeb3b13d9c8190b059d5c01518cf54 completed March 9, 2026, 11:49 a.m.
Created at: March 4, 2026, 7:44 p.m.