Triple

T13812258
Position Surface form Disambiguated ID Type / Status
Subject Ligne 2 E331921 entity
Predicate hasStation P35 FINISHED
Object Courcelles E1120380 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: Courcelles | Statement: [Ligne 2, hasStation, Courcelles]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Courcelles
Context triple: [Ligne 2, hasStation, Courcelles]
  • A. Courcelles chosen
    Courcelles is a district in Brussels, Belgium, known for being served by the city's metro system.
  • B. Gouvieux
    Gouvieux is a commune in northern France known for hosting the French residence of Aga Khan IV, Shah Karim al-Husayni.
  • C. Meyriez
    Meyriez is a small municipality in the canton of Fribourg in western Switzerland, situated on the shores of Lake Murten.
  • D. Douaumont
    Douaumont is a small commune in northeastern France best known for its World War I battlefield sites near Verdun, including major memorials and military cemeteries.
  • E. Rocourt
    Rocourt is a district of Liège in present-day Belgium, historically notable as the site of the 1746 Battle of Rocoux during the War of the Austrian Succession.
  • 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_69d81c59f8808190a851bc56afdc55e9 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de027198f8819095da3e714ac241f5 completed April 14, 2026, 9:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe64e47f1c8190a4ad09bc96d35b69 completed May 8, 2026, 10:34 p.m.
Created at: April 9, 2026, 10:12 p.m.