Triple

T2973405
Position Surface form Disambiguated ID Type / Status
Subject Heemstede E80335 entity
Predicate borderedBy P224 FINISHED
Object Haarlemmermeer E6265 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: Haarlemmermeer | Statement: [Heemstede, borderedBy, Haarlemmermeer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Haarlemmermeer
Context triple: [Heemstede, borderedBy, Haarlemmermeer]
  • A. Haarlemmermeer chosen
    Haarlemmermeer is a municipality in the province of North Holland in the Netherlands, best known for encompassing Amsterdam Airport Schiphol.
  • B. 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.
  • C. Volkerakmeer
    Volkerakmeer is a lake in the southwestern Netherlands that forms part of the Rhine–Meuse–Scheldt delta and serves as an important waterway and water management area.
  • D. Grevelingenmeer
    Grevelingenmeer is a large saltwater lake in the southwestern Netherlands, known for its water sports, nature reserves, and role in the Delta Works coastal defense system.
  • E. Braassemermeer
    Braassemermeer is a lake in the Dutch province of South Holland, known for recreational boating and water sports.
  • 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_69ad8b14ffe881908ffed62f9595c867 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad9987bb6c8190adfb447b76276962 completed March 8, 2026, 3:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69b12e27863881909c1c4b26e030e4bf completed March 11, 2026, 8:56 a.m.
Created at: March 8, 2026, 2:58 p.m.