Triple

T16114795
Position Surface form Disambiguated ID Type / Status
Subject Super universas E390974 entity
Predicate concerns P1256 FINISHED
Object city of Ypres E92602 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: city of Ypres | Statement: [Super universas, concerns, city of Ypres]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: city of Ypres
Context triple: [Super universas, concerns, city of Ypres]
  • A. Ypres chosen
    Ypres is a historic town in western Belgium that was the site of several major and devastating battles during World War I.
  • B. Armentières
    Armentières is a commune in northern France near the Belgian border, historically known for its textile industry and World War I significance.
  • C. Fromelles, France
    Fromelles, France is a small village in northern France best known as the site of a devastating World War I battle involving British and Australian forces.
  • D. Vimy, France
    Vimy, France is a commune in northern France best known as the site of the Canadian National Vimy Memorial commemorating World War I.
  • E. arrondissement of Ypres
    The arrondissement of Ypres is an administrative district in the Belgian province of West Flanders, centered on the historic city of Ypres and encompassing the surrounding municipalities.
  • 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_69d87f1a8dd881909f1de6ef78849874 completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e20169ce488190bbc814f23a3b7547 completed April 17, 2026, 9:46 a.m.
NED1 Entity disambiguation (via context triple) batch_69fff2a44cb48190abe3b1ea27349734 completed May 10, 2026, 2:51 a.m.
Created at: April 10, 2026, 5 a.m.