Triple

T6537523
Position Surface form Disambiguated ID Type / Status
Subject County of Zutphen E168200 entity
Predicate hasCity P316 FINISHED
Object Lochem E607047 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: Lochem | Statement: [County of Zutphen, hasCity, Lochem]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lochem
Context triple: [County of Zutphen, hasCity, Lochem]
  • A. Lochem chosen
    Lochem is a historic town and municipality in the Dutch province of Gelderland, known for its scenic countryside and location on the Twente Canal.
  • B. Doetinchem
    Doetinchem is a Dutch city in the eastern Netherlands, serving as a regional center in the Achterhoek area with a mix of historic charm and modern amenities.
  • C. Schoonhoven
    Schoonhoven is a historic Dutch town in South Holland, renowned for its silver craftsmanship and picturesque riverside setting.
  • D. Deurne
    Deurne is a district of the Belgian city of Antwerp, known for its residential neighborhoods and green spaces such as Rivierenhof park.
  • E. Gorinchem
    Gorinchem is a historic fortified city in the Netherlands known for its well-preserved city walls and picturesque old town.
  • 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_69c68a51564081909e93aee0dbd9cca3 completed March 27, 2026, 1:46 p.m.
NER Named-entity recognition batch_69c6add33acc8190bb0a9531648198f2 completed March 27, 2026, 4:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7941f24b881908aeb02b2cae78e12 completed March 28, 2026, 8:41 a.m.
Created at: March 27, 2026, 1:49 p.m.