Triple

T22025723
Position Surface form Disambiguated ID Type / Status
Subject Le Touret Memorial E543956 entity
Predicate locatedIn P40 FINISHED
Object Le Touret 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: Le Touret | Statement: [Le Touret Memorial, locatedIn, Le Touret]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Le Touret
Context triple: [Le Touret Memorial, locatedIn, Le Touret]
  • A. Le Touret chosen
    Le Touret is a village in northern France notable for its First World War cemeteries and memorials to fallen soldiers.
  • B. Seytroux
    Seytroux is a small mountain village and commune in the Haute-Savoie department of southeastern France, situated in the Chablais region of the French Alps.
  • C. Lantheuil
    Lantheuil is a small commune in the Calvados department of the Normandy region in northwestern France.
  • D. Larroquette
    Larroquette is the surname of John Larroquette, an American actor best known for his Emmy-winning role as Dan Fielding on the sitcom "Night Court."
  • E. Douaumont
    Douaumont is a small commune in northeastern France best known for its World War I battlefield sites near Verdun, including major memorials and military cemeteries.
  • 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_69e11e2e8ea4819084210fe06d3a1b8d completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f127cba61c8190a48ec2c1ee1315b0 completed April 28, 2026, 9:34 p.m.
Created at: April 16, 2026, 8:24 p.m.