Triple

T16829776
Position Surface form Disambiguated ID Type / Status
Subject Helder Expedition E409117 entity
Predicate location P40 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: [Helder Expedition, location, Texel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Texel
Context triple: [Helder Expedition, location, 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_69d88394566c8190b3dcbdc72935f7fa completed April 10, 2026, 4:59 a.m.
NER Named-entity recognition batch_69e3b315dbbc81908a1c83069e058770 completed April 18, 2026, 4:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00cfc366bc819084406ee88ddffe44 completed May 10, 2026, 6:34 p.m.
Created at: April 10, 2026, 5:23 a.m.