Triple

T23020787
Position Surface form Disambiguated ID Type / Status
Subject Brunssum E573155 entity
Predicate hasTwinTown P919 FINISHED
Object Alsdorf NE NERFINISHED

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: Alsdorf | Statement: [Brunssum, hasTwinTown, Alsdorf]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alsdorf
Context triple: [Brunssum, hasTwinTown, Alsdorf]
  • A. Alsdorf chosen
    Alsdorf is a town in western Germany’s North Rhine-Westphalia, historically shaped by coal mining and now part of the Aachen city region.
  • B. Asendorf
    Asendorf is a small municipality in Lower Saxony, Germany, known for its rural character and location within the Diepholz district.
  • C. Arnsdorf
    Arnsdorf is a small municipality in the German state of Saxony, known for its rural character and location near the city of Dresden.
  • D. Tasdorf
    Tasdorf is a small municipality in northern Germany notable as the birthplace of the 19th-century opera composer Giacomo Meyerbeer.
  • E. Aulendorf
    Aulendorf is a small town in the Upper Swabia region of southern Germany, known for its historic castle and spa facilities.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e245b821008190b0e09cb02092aae1 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f183e8324c81908b8868d298af66e1 completed April 29, 2026, 4:07 a.m.
Created at: April 17, 2026, 3:52 p.m.