Triple

T987565
Position Surface form Disambiguated ID Type / Status
Subject Flanders E21312 entity
Predicate contains P35 FINISHED
Object 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: Ypres | Statement: [Flanders, contains, Ypres]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ypres
Context triple: [Flanders, contains, 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. St. Vith
    St. Vith is a town in eastern Belgium that became a strategically important battleground during World War II, particularly noted for its role in the Battle of the Bulge.
  • C. Pontoise
    Pontoise is a historic commune in the northwestern suburbs of Paris, France, known for its picturesque setting on the River Oise and its association with Impressionist painters.
  • D. Verdun
    Verdun is a borough of Montreal, Quebec, known for its historic waterfront along the St. Lawrence River and its mix of residential neighborhoods and urban amenities.
  • E. Verdun, France
    Verdun, France is a historic northeastern French city on the Meuse River, best known as the site of one of World War I’s largest and bloodiest battles.
  • 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_69a493c383dc8190a03257f22d4b4183 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b4a7754c8190a10ba0587bd8323d completed March 1, 2026, 9:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac4289acc88190886ac8971297b1f8 completed March 7, 2026, 3:21 p.m.
Created at: March 1, 2026, 7:41 p.m.