Triple

T19162535
Position Surface form Disambiguated ID Type / Status
Subject Suisse normande E469090 entity
Predicate locatedNear P294 FINISHED
Object Caen NE NERFINISHED

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: Caen | Statement: [Suisse normande, locatedNear, Caen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Caen
Context triple: [Suisse normande, locatedNear, Caen]
  • A. Caen chosen
    Caen is a historic city in Normandy, France, known for its medieval architecture, ties to William the Conqueror, and its role in the World War II Normandy campaign.
  • B. Saint-Lô
    Saint-Lô is a historic town in northwestern France, known for its heavy destruction during World War II and its role as an administrative and commercial center in the Normandy region.
  • C. Cherbourg
    Cherbourg is a major French port city on the Cotentin Peninsula, known for its strategic naval harbor and cross-Channel ferry connections.
  • D. Cherbourg
    Cherbourg is a rural Aboriginal community in southern Queensland, Australia, known for its significant Indigenous history and culture.
  • E. Arromanches-les-Bains
    Arromanches-les-Bains is a coastal town in Normandy, France, best known for its role in the D-Day landings and the remains of the Mulberry artificial harbor just offshore.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8dd084ff48190ac0f8c46ee722629 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5eebe03ac8190bbe0b34ebf0d90c6 completed April 20, 2026, 9:15 a.m.
Created at: April 10, 2026, 12:06 p.m.