Triple

T2381694
Position Surface form Disambiguated ID Type / Status
Subject Saumur-Champigny E46324 entity
Predicate locatedNear P294 FINISHED
Object town of 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: town of Saumur | Statement: [Saumur-Champigny, locatedNear, town of Saumur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: town of Saumur
Context triple: [Saumur-Champigny, locatedNear, town of 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. Sully-sur-Loire
    Sully-sur-Loire is a historic commune in north-central France known for its medieval château overlooking the Loire River.
  • C. La Flèche
    La Flèche is a historic town in western France known for its royal heritage, educational institutions, and the renowned Zoo de La Flèche.
  • D. Saumur-Champigny
    Saumur-Champigny is a Loire Valley wine appellation in France renowned for producing elegant, aromatic red wines primarily from Cabernet Franc.
  • E. Lisieux
    Lisieux is a town and commune in the Calvados department of Normandy in northwestern France, known as a major Catholic pilgrimage site associated with Saint Thérèse of Lisieux.
  • 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_69a88a1554a48190a0180682bcf099be completed March 4, 2026, 7:37 p.m.
NER Named-entity recognition batch_69abc7b98c988190abdb4fe51bf65bde completed March 7, 2026, 6:37 a.m.
NED1 Entity disambiguation (via context triple) batch_69aea8b4f85c81909e5a4eda271b73ca completed March 9, 2026, 11:02 a.m.
Created at: March 4, 2026, 7:57 p.m.