Triple

T7711642
Position Surface form Disambiguated ID Type / Status
Subject Naaldwijk E174772 entity
Predicate locatedNear P294 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: [Naaldwijk, locatedNear, Wateringen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wateringen
Context triple: [Naaldwijk, locatedNear, 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_69c6995b3e8c8190833108f883d5f53c completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c702ae8b20819096930fe4be41b7be completed March 27, 2026, 10:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69ccec1cb5d48190ac9f6ad5920403f1 completed April 1, 2026, 9:57 a.m.
Created at: March 27, 2026, 4:04 p.m.