Triple

T3056913
Position Surface form Disambiguated ID Type / Status
Subject Province of Utrecht E60503 entity
Predicate containsAdministrativeTerritorialEntity P747 FINISHED
Object Nieuwegein E527408 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: Nieuwegein | Statement: [Province of Utrecht, containsAdministrativeTerritorialEntity, Nieuwegein]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nieuwegein
Context triple: [Province of Utrecht, containsAdministrativeTerritorialEntity, Nieuwegein]
  • A. Nieuwegein chosen
    Nieuwegein is a modern Dutch municipality and suburban city in the province of Utrecht, located just south of Utrecht along the Lek River.
  • B. Roosendaal
    Roosendaal is a city in the southern Netherlands known as a regional center for commerce and transport near the Belgian border.
  • C. Barendrecht
    Barendrecht is a suburban town in the western Netherlands, located just south of Rotterdam and known for its residential character and logistics industry.
  • D. Apeldoorn
    Apeldoorn is a city in the province of Gelderland in the Netherlands, known for the royal palace Het Loo and its historical ties to the Dutch monarchy.
  • E. Schoonhoven
    Schoonhoven is a historic Dutch town in South Holland, renowned for its silver craftsmanship and picturesque riverside setting.
  • 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_69ad8578137c81908259dcb27c7d6d7c completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ad9e13f16c81909e11ed1444c71151 completed March 8, 2026, 4:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69c9742fd0dc8190a154cf83c87eb508 completed March 29, 2026, 6:49 p.m.
Created at: March 8, 2026, 3:02 p.m.