Triple

T9218382
Position Surface form Disambiguated ID Type / Status
Subject Luxembourg Province E221297 entity
Predicate containsCity P294 FINISHED
Object Bastogne E6658 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: Bastogne | Statement: [Luxembourg Province, containsCity, Bastogne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bastogne
Context triple: [Luxembourg Province, containsCity, Bastogne]
  • A. Bastogne chosen
    Bastogne is a town in southeastern Belgium best known for its strategic role and fierce fighting during World War II’s Battle of the Bulge.
  • 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. Beauvechain
    Beauvechain is a municipality in Walloon Brabant, Belgium, known for its rural character and the presence of a major Belgian Air Component base.
  • D. Lannesdorf
    Lannesdorf is a residential subdistrict of the Bad Godesberg borough in the city of Bonn, Germany.
  • E. Gravelotte
    Gravelotte is a village in northeastern France best known as the site of a major 1870 Franco-Prussian War battle.
  • 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_69ca83eae42c8190a0ea9e040710a277 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccda730f688190b64b2cc8c4898ac3 completed April 1, 2026, 8:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69d0662427dc81908cb9bfacc5b9e0f5 completed April 4, 2026, 1:15 a.m.
Created at: March 30, 2026, 7:27 p.m.