Triple

T91826
Position Surface form Disambiguated ID Type / Status
Subject Luxembourg E1844 entity
Predicate capital P234 FINISHED
Object Luxembourg City E1844 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: Luxembourg City | Statement: [Luxembourg, capital, Luxembourg City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Luxembourg City
Context triple: [Luxembourg, capital, Luxembourg City]
  • A. Luxembourg chosen
    Luxembourg is a small, landlocked Western European country known for its prosperous economy, status as a major financial center, and role as a founding member of the European Union.
  • B. Strasbourg
    Strasbourg is a major French city on the Rhine known for hosting key European institutions, including the European Parliament and the Council of Europe.
  • C. Brussels, Belgium
    Brussels, Belgium is the capital city of Belgium and a major political center of Europe, hosting key institutions such as the European Union and numerous international organizations.
  • D. Vilvoorde
    Vilvoorde is a city in the Flemish Region of Belgium, located just north of Brussels and known as part of the capital’s broader metropolitan area.
  • E. Lille
    Lille is a historic industrial and cultural hub in northern France, known for its Flemish-influenced architecture, large student population, and role as a major European transport crossroads.
  • 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_69a24d1a97dc819094e6c021fe9b05a7 completed Feb. 28, 2026, 2:04 a.m.
NER Named-entity recognition batch_69a24faa6d608190920c8fc144e85e21 completed Feb. 28, 2026, 2:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69a34d8edb8c81909c7229fe6e4c0569 completed Feb. 28, 2026, 8:18 p.m.
Created at: Feb. 28, 2026, 2:07 a.m.