Triple

T3413384
Position Surface form Disambiguated ID Type / Status
Subject Noord-Beveland E71951 entity
Predicate hasPart P35 FINISHED
Object Geersdijk E415610 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: Geersdijk | Statement: [Noord-Beveland, hasPart, Geersdijk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Geersdijk
Context triple: [Noord-Beveland, hasPart, Geersdijk]
  • A. Nieuwendijk
    Nieuwendijk is one of Amsterdam’s oldest and busiest shopping streets, running through the historic city center near Dam Square.
  • B. Vollenhove
    Vollenhove is a historic town in the Dutch province of Overijssel, known for its former status as a regional administrative and noble center with several notable estates and churches.
  • C. Scharendijke chosen
    Scharendijke is a village in the Dutch province of Zeeland, known as a popular base for water sports and diving in the Grevelingen and North Sea area.
  • D. Veldhoven
    Veldhoven is a town and municipality in the southern Netherlands, located near Eindhoven in the province of North Brabant.
  • E. Leusden
    Leusden is a Dutch town and municipality in the central Netherlands, known for its green residential character and proximity to the city of Amersfoort.
  • 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_69ad85ac312481909e7027ced1456a9f completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb90ba83c81909abdcddb334e64f6 completed March 8, 2026, 5:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69c669cd6bb08190966b89a2129f5738 completed March 27, 2026, 11:28 a.m.
Created at: March 8, 2026, 3:15 p.m.