Triple

T19507234
Position Surface form Disambiguated ID Type / Status
Subject Mook E488053 entity
Predicate hasNearbyWaterBody P1489 FINISHED
Object Maasplassen NE NERFINISHED

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: Maasplassen | Statement: [Mook, hasNearbyWaterBody, Maasplassen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maasplassen
Context triple: [Mook, hasNearbyWaterBody, Maasplassen]
  • A. Mookerplas chosen
    Mookerplas is a recreational lake in the Dutch province of Limburg, popular for swimming, water sports, and nature activities.
  • B. Binnenmaas
    Binnenmaas was a former municipality in the Dutch province of South Holland, named after the nearby lake and comprising several villages in the Hoeksche Waard region.
  • C. Maasmechelen
    Maasmechelen is a municipality in the Belgian province of Limburg, known for its proximity to the Meuse River and the popular Maasmechelen Village outlet shopping center.
  • D. Galmaarden
    Galmaarden is a small Dutch-speaking municipality in the Flemish Brabant province of Belgium, known for its rural character and location near the language border.
  • E. 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.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e8d9d1c88190b01cd78b8be49384 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e635130e708190bb3d70e1abbade2a completed April 20, 2026, 2:15 p.m.
Created at: April 10, 2026, 1:40 p.m.