Triple

T13324598
Position Surface form Disambiguated ID Type / Status
Subject Beauvais–Tillé Airport E317405 entity
Predicate serves P98 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: [Beauvais–Tillé Airport, serves, Beauvais]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Beauvais
Context triple: [Beauvais–Tillé Airport, serves, 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_69d806b4d62c81908d4ced1665414be5 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d9992c1fec8190bcb6a6bb3c973a24 completed April 11, 2026, 12:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69fd8a9c41908190b789765861bd9924 completed May 8, 2026, 7:02 a.m.
Created at: April 9, 2026, 9:30 p.m.