Triple

T3388687
Position Surface form Disambiguated ID Type / Status
Subject Kwintsheul E71364 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: [Kwintsheul, locatedNear, Wateringen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wateringen
Context triple: [Kwintsheul, 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. Maassluis
    Maassluis is a historic port town in the province of South Holland in the Netherlands, situated along the Nieuwe Waterweg west of Rotterdam.
  • C. Oranjewoud
    Oranjewoud is a historic estate and village in the Dutch province of Friesland, long associated with the royal House of Orange-Nassau.
  • D. Papendrecht
    Papendrecht is a Dutch town situated on the river Merwede in the province of South Holland, known for its residential character and proximity to the city of Dordrecht.
  • E. Honselersdijk
    Honselersdijk is a village in the Dutch province of South Holland, known for its greenhouse horticulture and proximity to The Hague.
  • 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_69ad85a8fd9c819095ecedf838d2bf1b completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb665c6008190b33994ef20f5bd61 completed March 8, 2026, 5:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69c65f9d763c81908bdc6d9cfc718a55 completed March 27, 2026, 10:44 a.m.
Created at: March 8, 2026, 3:14 p.m.