Triple

T9218445
Position Surface form Disambiguated ID Type / Status
Subject Luxembourg Province E221297 entity
Predicate administrativeCenter P1474 FINISHED
Object Arlon E154217 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: Arlon | Statement: [Luxembourg Province, administrativeCenter, Arlon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Arlon
Context triple: [Luxembourg Province, administrativeCenter, Arlon]
  • A. Arlon chosen
    Arlon is a historic town in southeastern Belgium that serves as the capital of the province of Luxembourg in the Walloon Region.
  • B. Porrentruy
    Porrentruy is a historic town in northwestern Switzerland known for its medieval castle and role as a regional center in the canton of Jura.
  • C. Bossey
    Bossey is a small French commune in the Haute-Savoie department of the Auvergne-Rhône-Alpes region, located near the Swiss border south of Geneva.
  • D. Schorisse
    Schorisse is a village in East Flanders, Belgium, that now forms part of the municipality of Maarkedal.
  • E. Bogis-Bossey
    Bogis-Bossey is a small municipality in the canton of Vaud in western Switzerland, situated near Lake Geneva and close to the French border.
  • 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_69d0b1ba860c8190b621b9fe88bc6ba2 completed April 4, 2026, 6:37 a.m.
Created at: March 30, 2026, 7:27 p.m.