Triple

T17314192
Position Surface form Disambiguated ID Type / Status
Subject Musée Antoine Lécuyer E420377 entity
Predicate touristAttraction P530 FINISHED
Object Saint-Quentin 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: Saint-Quentin | Statement: [Musée Antoine Lécuyer, touristAttraction, Saint-Quentin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Saint-Quentin
Context triple: [Musée Antoine Lécuyer, touristAttraction, Saint-Quentin]
  • A. Saint-Quentin chosen
    Saint-Quentin is a historic town in northern France known for its Gothic basilica, Art Deco architecture, and role as a regional administrative and commercial center.
  • B. Mézières
    Mézières is a French town historically known as a military and engineering education center, notably associated with the prestigious École royale du génie.
  • C. Soissons
    Soissons is a historic town in northern France known for its strategic military importance and notable battles throughout European history.
  • D. Château-Thierry
    Château-Thierry is a historic town in northern France known for its World War I battlefields and its association with the poet Jean de La Fontaine.
  • E. Vic-sur-Aisne
    Vic-sur-Aisne is a commune in the Aisne department of northern France, known for its riverside setting and historic architecture.
  • 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_69d889d22b848190a4663d0b8f8f76e7 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e4399b4dcc8190996d79d04ba88795 completed April 19, 2026, 2:10 a.m.
Created at: April 10, 2026, 5:43 a.m.