Triple

T15597392
Position Surface form Disambiguated ID Type / Status
Subject Rasta Vechta E374937 entity
Predicate homeCity P263 FINISHED
Object Vechta E217603 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: Vechta | Statement: [Rasta Vechta, homeCity, Vechta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vechta
Context triple: [Rasta Vechta, homeCity, Vechta]
  • A. Vechta chosen
    Vechta is a town in Lower Saxony, Germany, known for its historical significance, university, and annual Stoppelmarkt fair.
  • B. Sappemeer
    Sappemeer is a town in the province of Groningen in the northeastern Netherlands, historically known for its peat colonies and waterways.
  • C. Zwalm
    Zwalm is a rural municipality in East Flanders, Belgium, known for its scenic hilly landscape, watermills, and network of walking and cycling routes.
  • D. Salland
    Salland is a historical and rural region in the Dutch province of Overijssel, known for its scenic landscapes, small towns, and agricultural character.
  • E. Oostzaan
    Oostzaan is a small municipality in the province of North Holland in the Netherlands, located just north of Amsterdam.
  • 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_69d85cce25008190b13b52745fbd719b completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04e609ab081909feb486a57439960 completed April 16, 2026, 2:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff678821a481908378db1ffc76ba05 completed May 9, 2026, 4:57 p.m.
Created at: April 10, 2026, 4:12 a.m.