Triple

T15022701
Position Surface form Disambiguated ID Type / Status
Subject Château Gaillard E378125 entity
Predicate department P1467 FINISHED
Object Eure E583530 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: Eure | Statement: [Château Gaillard, department, Eure]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eure
Context triple: [Château Gaillard, department, Eure]
  • A. Eure
    Eure is a river in northern France that flows through the regions of Normandy and Centre-Val de Loire before joining the Seine.
  • B. Eure chosen
    Eure is a department in the Normandy region of northern France, known for its rural landscapes, historic towns, and proximity to Paris.
  • C. Eure River
    The Eure River is a tributary of the Seine in northern France that flows through the city of Chartres and several other towns in the Normandy and Centre-Val de Loire regions.
  • D. Jever
    Jever is a historic town in Lower Saxony, Germany, best known for its traditional North German architecture and the Jever Pilsener brewery.
  • E. Rheinau
    Rheinau is a district of Mannheim in the German state of Baden-Württemberg, known for its residential areas and proximity to the Rhine.
  • 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_69d85cd3a3c881908c71fc424d459c17 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded765462c819097f331c9b39c80e3 completed April 15, 2026, 12:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe9dd2c96c8190a0368678584aaa16 completed May 9, 2026, 2:37 a.m.
Created at: April 10, 2026, 2:56 a.m.