Triple

T4124197
Position Surface form Disambiguated ID Type / Status
Subject Calvados department E92684 entity
Predicate contains P35 FINISHED
Object Lisieux E230690 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: Lisieux | Statement: [Calvados department, contains, Lisieux]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lisieux
Context triple: [Calvados department, contains, Lisieux]
  • A. Lisieux chosen
    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.
  • B. Saint-Mard
    Saint-Mard is a French commune in the Seine-et-Marne department in the Île-de-France region, northeast of Paris.
  • C. Langres
    Langres is a historic fortified town in northeastern France known for its well-preserved ramparts and as the birthplace of Enlightenment philosopher Denis Diderot.
  • D. Remigny
    Remigny is a small wine-producing village in the Burgundy region of eastern France, situated near the renowned appellation of Santenay.
  • E. Saint-Pol-de-Léon
    Saint-Pol-de-Léon is a historic coastal town in Brittany, northwestern France, known for its Gothic cathedral and vegetable-growing region.
  • 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_69aed9685f70819086932777aec8d959 completed March 9, 2026, 2:30 p.m.
NER Named-entity recognition batch_69af0208903c8190a7f451a455d3e253 completed March 9, 2026, 5:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69bde03b1f508190b9d5026103d3ee79 completed March 21, 2026, 12:03 a.m.
Created at: March 9, 2026, 3:41 p.m.