Triple

T16686257
Position Surface form Disambiguated ID Type / Status
Subject Vlieland E405468 entity
Predicate borderedBy P224 FINISHED
Object Texel E160304 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: Texel | Statement: [Vlieland, borderedBy, Texel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Texel
Context triple: [Vlieland, borderedBy, Texel]
  • A. Texel chosen
    Texel is the largest and most populated of the West Frisian Islands off the northwestern coast of the Netherlands, known for its beaches, dunes, and nature reserves.
  • B. Vlieland
    Vlieland is a sparsely populated Dutch Wadden Sea island known for its wide beaches, dunes, and car-free, nature-focused tourism.
  • C. Ameland
    Ameland is a Dutch Wadden Sea island known for its sandy beaches, dunes, and nature reserves, popular as a holiday destination in the northern Netherlands.
  • D. Kennemerland
    Kennemerland is a coastal historical region in the northwest of the Netherlands, known for its dunes, beaches, and old trading towns.
  • E. Opsterland
    Opsterland is a municipality in the province of Friesland in the northern Netherlands, known for its rural landscape and small villages.
  • 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_69d8838c28748190b3f5967c743940ab completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e37ea63b7081908a055036172f9683 completed April 18, 2026, 12:52 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00c79657ec8190b1b3500b7a99df0a completed May 10, 2026, 5:59 p.m.
Created at: April 10, 2026, 5:19 a.m.