Triple

T2154399
Position Surface form Disambiguated ID Type / Status
Subject Oise E47853 entity
Predicate passesThroughCity P416 FINISHED
Object Beauvais E343358 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: Beauvais | Statement: [Oise, passesThroughCity, Beauvais]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Beauvais
Context triple: [Oise, passesThroughCity, Beauvais]
  • A. Beauvais chosen
    Beauvais is a historic city in northern France known for its impressive Gothic cathedral and role as the capital of the Oise department.
  • B. Creil
    Creil is a commuter town in northern France’s Oise department, known as a regional rail hub connecting Paris with Picardy via major train and RER lines.
  • C. Reims
    Reims is a historic city in northeastern France known for its Gothic cathedral, role in French coronations, and significance during both World Wars.
  • D. Houilles
    Houilles is a suburban commune in north-central France, located in the western outskirts of Paris within the Yvelines department.
  • E. Valenciennes
    Valenciennes is a historic industrial city in northern France near the Belgian border, known for its former coal and steel industries and its rich artistic and architectural heritage.
  • 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_69a88a1d1fd8819088b34990d69a712f completed March 4, 2026, 7:38 p.m.
NER Named-entity recognition batch_69abbe64fdf081909a5ea6818bddd18c completed March 7, 2026, 5:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69b2f39ad7488190a7604a113c2e2bb3 completed March 12, 2026, 5:10 p.m.
Created at: March 4, 2026, 7:44 p.m.