Triple

T4983194
Position Surface form Disambiguated ID Type / Status
Subject Veerse Gatdam E111936 entity
Predicate protects P1040 FINISHED
Object Veerse Meer lagoon E358116 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: Veerse Meer lagoon | Statement: [Veerse Gatdam, protects, Veerse Meer lagoon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Veerse Meer lagoon
Context triple: [Veerse Gatdam, protects, Veerse Meer lagoon]
  • A. Veerse Meer chosen
    Veerse Meer is a coastal lagoon and recreational lake in the Dutch province of Zeeland, popular for water sports and nature conservation.
  • B. Markiezaatsmeer
    Markiezaatsmeer is a Dutch lake and nature reserve in the province of North Brabant, known for its wetlands and rich birdlife.
  • C. Haarlemmermeer
    Haarlemmermeer is a municipality in the province of North Holland in the Netherlands, best known for encompassing Amsterdam Airport Schiphol.
  • D. Braassemermeer
    Braassemermeer is a lake in the Dutch province of South Holland, known for recreational boating and water sports.
  • E. Oldambtmeer
    Oldambtmeer is an artificial lake in the municipality of Oldambt in the province of Groningen, Netherlands, created as part of a large-scale landscape and recreational development project.
  • 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_69bd441adc208190b70a033a0741d01e completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd725489bc81908f660332e25f29cf completed March 20, 2026, 4:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69be8a13f5448190a49f914d1ba49a7a completed March 21, 2026, 12:07 p.m.
Created at: March 20, 2026, 1:33 p.m.