Triple

T16742375
Position Surface form Disambiguated ID Type / Status
Subject Armistice Clearing memorials E406863 entity
Predicate near P350 FINISHED
Object Compiègne E173943 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: Compiègne | Statement: [Armistice Clearing memorials, near, Compiègne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Compiègne
Context triple: [Armistice Clearing memorials, near, Compiègne]
  • A. Compiegne chosen
    Compiègne is a historic city in northern France known for its royal château, forest, and role in significant events such as the signing of the 1918 Armistice.
  • 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. Lubersac
    Lubersac is a small commune in the Corrèze department of south-central France, known for its rural character and traditional Limousin heritage.
  • E. Soissons
    Soissons is a historic town in northern France known for its strategic military importance and notable battles throughout European history.
  • 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_69d8838ffb088190a0b11149929006bf completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e39c3f49808190b543d8da34031f3d completed April 18, 2026, 2:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00aaf3c6088190a8301a9613d74474 completed May 10, 2026, 3:57 p.m.
Created at: April 10, 2026, 5:21 a.m.