Triple

T10399550
Position Surface form Disambiguated ID Type / Status
Subject Oise E245108 entity
Predicate capital P234 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, capital, Beauvais]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Beauvais
Context triple: [Oise, capital, 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_69d381b5116081908d85227bab6d3c0c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e9d2e8488190b2bb8f8509903804 completed April 7, 2026, 11:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69d9987838ac8190a6ba09305fc27621 completed April 11, 2026, 12:40 a.m.
Created at: April 6, 2026, 12:07 p.m.