Triple

T7462784
Position Surface form Disambiguated ID Type / Status
Subject Ockelbo Municipality E176292 entity
Predicate seat P75 FINISHED
Object Ockelbo E176292 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: Ockelbo | Statement: [Ockelbo Municipality, seat, Ockelbo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ockelbo
Context triple: [Ockelbo Municipality, seat, Ockelbo]
  • A. Korsholm
    Korsholm is a coastal municipality in western Finland, known for its largely Swedish-speaking population and proximity to the city of Vaasa in the Ostrobothnia region.
  • B. Rudkøbing
    Rudkøbing is a small historic town on the Danish island of Langeland, known for its well-preserved old streets and as the birthplace of physicist Hans Christian Ørsted.
  • C. Ockelbo Municipality chosen
    Ockelbo Municipality is a rural municipality in Gävleborg County, Sweden, known for its forests, lakes, and outdoor recreation opportunities.
  • D. Lysekil
    Lysekil is a coastal town in western Sweden known for its picturesque archipelago, fishing heritage, and popular seaside tourism.
  • E. Havelberg
    Havelberg is a small historic town in Saxony-Anhalt, Germany, known for its medieval cathedral and location at the confluence of the Havel and Elbe rivers.
  • 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_69c69f21632481908bf83f6c6da897e3 completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f3d80ae08190ba383066cf0cb2ce completed March 27, 2026, 9:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69c83c5f1f408190a7d42abe28605ddb completed March 28, 2026, 8:38 p.m.
Created at: March 27, 2026, 3:39 p.m.