Triple

T710632
Position Surface form Disambiguated ID Type / Status
Subject Gelderland E14197 entity
Predicate borders P224 FINISHED
Object Overijssel E14902 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: Overijssel | Statement: [Gelderland, borders, Overijssel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Overijssel
Context triple: [Gelderland, borders, Overijssel]
  • A. Overijssel chosen
    Overijssel is a province in the eastern Netherlands known for its historic Hanseatic cities, rivers, and varied landscapes of forests, heathlands, and farmland.
  • B. Gelderland
    Gelderland is a large province in the eastern Netherlands known for its varied landscapes, including the forested Veluwe region and the river areas along the Rhine, Waal, and IJssel.
  • C. North Holland
    North Holland is a province in the western Netherlands known for encompassing the national capital, Amsterdam, as well as historic towns and North Sea coastline.
  • D. Zuid-Holland
    Zuid-Holland is a densely populated coastal province in the western Netherlands that includes major cities such as Rotterdam and The Hague.
  • E. Zeeland
    Zeeland is a coastal province in the southwest of the Netherlands, known for its islands, peninsulas, and extensive dike and flood defense systems.
  • 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_69a493494ec48190ae6751683625a9ba completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a55c99fc8190941c5fd18551792a completed March 1, 2026, 8:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69ace5371c2c8190861a5cbf9d089e4f completed March 8, 2026, 2:55 a.m.
Created at: March 1, 2026, 7:36 p.m.