Triple

T13543951
Position Surface form Disambiguated ID Type / Status
Subject De Bilt E323463 entity
Predicate contains P35 FINISHED
Object Bilthoven NE NERFINISHED

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: Bilthoven | Statement: [De Bilt, contains, Bilthoven]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bilthoven
Context triple: [De Bilt, contains, Bilthoven]
  • A. Bilthoven chosen
    Bilthoven is a town in the Dutch province of Utrecht, known as a residential suburb with good rail connections and several national research institutes.
  • B. Veldhoven
    Veldhoven is a town and municipality in the southern Netherlands, located near Eindhoven in the province of North Brabant.
  • C. Schoonhoven
    Schoonhoven is a historic Dutch town in South Holland, renowned for its silver craftsmanship and picturesque riverside setting.
  • D. Kloosterburen
    Kloosterburen is a small village in the Dutch province of Groningen, known for its historic churches and rural character.
  • E. Zundert
    Zundert is a municipality and town in the southern Netherlands, known as the birthplace of painter Vincent van Gogh and for hosting one of the world's largest flower parades.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8076776248190bdf0d4fa1f85a5fc completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbafda36248190acabde65a88c5471 completed April 12, 2026, 2:44 p.m.
Created at: April 9, 2026, 9:45 p.m.