Triple

T10891631
Position Surface form Disambiguated ID Type / Status
Subject Wormerland E257190 entity
Predicate hasNeighboringMunicipality P224 FINISHED
Object Landsmeer E257189 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: Landsmeer | Statement: [Wormerland, hasNeighboringMunicipality, Landsmeer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Landsmeer
Context triple: [Wormerland, hasNeighboringMunicipality, Landsmeer]
  • A. Landsmeer chosen
    Landsmeer is a small Dutch town and municipality in North Holland, situated just north of Amsterdam and known for its watery landscapes and nature reserves.
  • B. Maasland
    Maasland is a historical region in the Low Countries centered along the river Meuse, known for its medieval political and cultural significance.
  • C. Zoutelande
    Zoutelande is a coastal village and popular seaside resort in the Dutch province of Zeeland, known for its beaches and dunes along the North Sea.
  • D. Scherpenzeel
    Scherpenzeel is a small Dutch municipality in the province of Gelderland, known for its rural character and historic village center.
  • E. Zwanenburg
    Zwanenburg is a village in North Holland, Netherlands, situated near Amsterdam and known as a suburban residential community within the Haarlemmermeer municipality.
  • 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_69d6aa8550c8819095508a2ed9acf3db completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d7520550c4819081296546c8f534f1 completed April 9, 2026, 7:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69e2169ea02c8190addf125ec5adafe8 completed April 17, 2026, 11:16 a.m.
Created at: April 8, 2026, 9:21 p.m.