Triple

T9316228
Position Surface form Disambiguated ID Type / Status
Subject Normandy (administrative region) E224127 entity
Predicate contains P35 FINISHED
Object Bayeux E105080 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: Bayeux | Statement: [Normandy (administrative region), contains, Bayeux]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bayeux
Context triple: [Normandy (administrative region), contains, Bayeux]
  • A. Bayeux
    Bayeux is a municipality in the Brazilian state of Paraíba, located in the northeastern region of the country and forming part of the João Pessoa metropolitan area.
  • B. Bayeux chosen
    Bayeux is a historic town in Normandy, France, renowned for the medieval Bayeux Tapestry and its proximity to the D-Day landing beaches.
  • C. Beauvais
    Beauvais is a historic city in northern France known for its impressive Gothic cathedral and role as the capital of the Oise department.
  • D. Calais
    Calais is a major French port city on the northern coast, serving as one of the primary crossing points between France and England.
  • E. Calais
    Calais is a figure from Greek mythology, one of the winged sons of Boreas who joined Jason and the Argonauts on their legendary voyage.
  • 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_69ca8425f4fc81909c1c586e9a5b7530 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd358846e48190a8aacfab19d88ae7 completed April 1, 2026, 3:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69d0c7acba54819086da668f234321de completed April 4, 2026, 8:11 a.m.
Created at: March 30, 2026, 7:37 p.m.