Triple

T5583772
Position Surface form Disambiguated ID Type / Status
Subject Warwick E146701 entity
Predicate hasTwinTown P919 FINISHED
Object Saumur E229371 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: Saumur | Statement: [Warwick, hasTwinTown, Saumur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Saumur
Context triple: [Warwick, hasTwinTown, Saumur]
  • A. Saumur chosen
    Saumur is a historic town in western France renowned for its château, wine production, and cavalry school on the banks of the Loire River.
  • B. Blois
    Blois is a historic city in central France known for its Renaissance château, picturesque setting on the Loire River, and rich royal heritage.
  • C. Angoulême
    Angoulême is a historic city in southwestern France known for its hilltop old town, medieval ramparts, and status as a major center of the French comics industry.
  • D. Bourges
    Bourges is a historic city in central France known for its well-preserved medieval architecture and its UNESCO-listed Gothic cathedral, Saint-Étienne.
  • E. Châteaubriant
    Châteaubriant is a historic town in western France known for its medieval castle and role as a local administrative and cultural center.
  • 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_69c0090287a08190b4098411effe970c completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c02084b5f0819089b62283c57704ec completed March 22, 2026, 5:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69c02862bd048190b9db0fd3f3562da2 completed March 22, 2026, 5:35 p.m.
Created at: March 22, 2026, 3:37 p.m.