Triple

T10915590
Position Surface form Disambiguated ID Type / Status
Subject Saumur campus E257813 entity
Predicate locatedIn P40 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: [Saumur campus, locatedIn, Saumur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Saumur
Context triple: [Saumur campus, locatedIn, 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. Saintes
    Saintes is a historic town in southwestern France, known for its well-preserved Roman and medieval heritage, including ancient monuments and religious sites.
  • C. Blois
    Blois is a historic city in central France known for its Renaissance château, picturesque setting on the Loire River, and rich royal heritage.
  • D. 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.
  • E. Bourges
    Bourges is a historic city in central France known for its well-preserved medieval architecture and its UNESCO-listed Gothic cathedral, Saint-Étienne.
  • 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_69d6aa864ed88190818280ab6791d065 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d77074c77c8190af91369eee11f1b7 completed April 9, 2026, 9:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69f6d5e2b0408190866bbe9a3a56928b completed May 3, 2026, 4:58 a.m.
Created at: April 8, 2026, 9:22 p.m.