Triple

T14186209
Position Surface form Disambiguated ID Type / Status
Subject municipality of Westland E351583 entity
Predicate containsSettlement P847 FINISHED
Object Wateringen E205642 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: Wateringen | Statement: [municipality of Westland, containsSettlement, Wateringen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wateringen
Context triple: [municipality of Westland, containsSettlement, Wateringen]
  • A. Wateringen chosen
    Wateringen is a town in the western Netherlands that forms part of the municipality of Westland in the province of South Holland.
  • B. Meerssen
    Meerssen is a historic town and municipality in the Dutch province of Limburg, known for its medieval basilica and scenic location near Maastricht.
  • C. Valkenswaard
    Valkenswaard is a town in the southern Netherlands known for its strong equestrian culture and international show jumping events.
  • D. Woensdrecht
    Woensdrecht is a municipality in the Dutch province of North Brabant, known for its strategic location near the Belgian border and its military air base.
  • E. Esens
    Esens is a small historic town in Lower Saxony, Germany, known for its coastal North Sea location and traditional East Frisian character.
  • 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_69d8278834a08190b0f1784e58d7b99c completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de61cd5778819092a03597bcdcc182 completed April 14, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd32497780819092e2d2ffe2a9dcaf completed May 8, 2026, 12:46 a.m.
Created at: April 10, 2026, 1:03 a.m.