Triple

T5649324
Position Surface form Disambiguated ID Type / Status
Subject Poppa of Bayeux E124462 entity
Predicate associatedWith P37 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: [Poppa of Bayeux, associatedWith, Bayeux]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bayeux
Context triple: [Poppa of Bayeux, associatedWith, Bayeux]
  • A. 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.
  • B. 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.
  • 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. Thérouanne
    Thérouanne is a historic town in northern France that once served as an important medieval religious center and episcopal seat.
  • 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_69c00825df388190a58742fa9b1aa33d completed March 22, 2026, 3:17 p.m.
NER Named-entity recognition batch_69c022d2ed648190a5152c8668cbda02 completed March 22, 2026, 5:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69c04d8cea4481908fccb8ed102b18a1 completed March 22, 2026, 8:14 p.m.
Created at: March 22, 2026, 3:42 p.m.