Triple

T13543907
Position Surface form Disambiguated ID Type / Status
Subject Soest E323462 entity
Predicate hasSettlement P1068 FINISHED
Object Soestduinen E504658 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: Soestduinen | Statement: [Soest, hasSettlement, Soestduinen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Soestduinen
Context triple: [Soest, hasSettlement, Soestduinen]
  • A. Loosduinen
    Loosduinen is a district in the southwest of The Hague in the Netherlands, historically a separate village known for its former abbey and more rural character.
  • B. Voorne aan Zee
    Voorne aan Zee is a municipality in the Dutch province of South Holland that includes the historic port town of Hellevoetsluis and other nearby communities on the island of Voorne.
  • C. Heinkenszand
    Heinkenszand is a village in the Dutch province of Zeeland that serves as a local center within the South Beveland region.
  • D. Londerzeel
    Londerzeel is a municipality in the Flemish Brabant province of Belgium, known for its residential character and proximity to both Brussels and Antwerp.
  • E. Soesterduinen chosen
    Soesterduinen is a scenic sand dune and heathland nature area in the Netherlands, popular for walking, cycling, and outdoor recreation.
  • 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_69d8076776248190bdf0d4fa1f85a5fc completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbafda36248190acabde65a88c5471 completed April 12, 2026, 2:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69f75da094288190aff108b006c3da1f completed May 3, 2026, 2:37 p.m.
Created at: April 9, 2026, 9:45 p.m.