Triple

T17134613
Position Surface form Disambiguated ID Type / Status
Subject Ninove E415802 entity
Predicate hasTwinTown P919 FINISHED
Object Aalborg E201878 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: Aalborg | Statement: [Ninove, hasTwinTown, Aalborg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aalborg
Context triple: [Ninove, hasTwinTown, Aalborg]
  • A. Aalborg chosen
    Aalborg is a major city in northern Denmark known for its historic architecture, vibrant cultural life, and role as a regional economic and educational center.
  • B. Aarhus
    Aarhus is Denmark’s second-largest city, a major cultural and economic center on the Jutland peninsula known for its universities, vibrant arts scene, and historic harbor.
  • C. Kolding
    Kolding is a historic Danish city in Southern Jutland known for Koldinghus Castle, its fjord-side location, and its role as a regional cultural and educational center.
  • D. Esbjerg
    Esbjerg is a major Danish port city on the North Sea, known for its offshore oil and wind industry, maritime heritage, and role as a regional economic center in western Jutland.
  • E. Randers
    Randers is a historic market town and one of the largest cities in eastern Jutland, Denmark, known for its old town center and location along the Gudenå River.
  • 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_69d886d15af4819092f92f8a129763e6 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3f02dca8881908efd73741397a207 completed April 18, 2026, 8:57 p.m.
NED1 Entity disambiguation (via context triple) batch_6a01482cd918819082d18b3cb76394cb completed May 11, 2026, 3:08 a.m.
Created at: April 10, 2026, 5:36 a.m.