Triple

T5500707
Position Surface form Disambiguated ID Type / Status
Subject Geoffrey V Plantagenet E144318 entity
Predicate placeOfMarriage P128 FINISHED
Object Le Mans E43233 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: Le Mans | Statement: [Geoffrey V Plantagenet, placeOfMarriage, Le Mans]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Le Mans
Context triple: [Geoffrey V Plantagenet, placeOfMarriage, Le Mans]
  • A. Le Mans chosen
    Le Mans is a historic city in northwestern France best known for its annual 24 Hours of Le Mans endurance sports car race.
  • B. Montlhéry
    Montlhéry is a commune in northern France best known for its historic motor racing circuit, the Autodrome de Linas-Montlhéry.
  • C. Deauzya
    Deauzya is the given first name of American professional basketball player DiDi Richards.
  • D. Arques
    Arques is a river in northern France that flows through the Normandy region and reaches the English Channel at the port city of Dieppe.
  • E. Le Mans metropolitan area
    The Le Mans metropolitan area is an urban and economic hub in western France centered on the city of Le Mans, renowned for its automotive industry and the 24 Hours of Le Mans endurance race.
  • 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_69c008f5a2748190bce7a39aabf87a6d completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c01f08c2a4819093e772a1497c7ecc completed March 22, 2026, 4:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0279bff0481908b157a09499e8610 completed March 22, 2026, 5:32 p.m.
Created at: March 22, 2026, 3:32 p.m.