Triple

T2296477
Position Surface form Disambiguated ID Type / Status
Subject Low Countries E51626 entity
Predicate hasPart P35 FINISHED
Object Friesland E15439 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: Friesland | Statement: [Low Countries, hasPart, Friesland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Friesland
Context triple: [Low Countries, hasPart, Friesland]
  • A. Friesland chosen
    Friesland is a northern province of the Netherlands known for its distinct Frisian language, rich maritime history, and unique cultural traditions.
  • B. Zeeland
    Zeeland is a coastal province in the southwest of the Netherlands, known for its islands, peninsulas, and extensive dike and flood defense systems.
  • C. Drenthe, Netherlands
    Drenthe, Netherlands is a rural northeastern Dutch province known for its prehistoric dolmen tombs, extensive nature reserves, and quiet agricultural landscapes.
  • D. Holland
    Holland is a common English surname of Dutch origin, historically referring to people from the Holland region of the Netherlands.
  • E. Texel
    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.
  • 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_69a88b0a9f248190bcff941463d8f65a completed March 4, 2026, 7:42 p.m.
NER Named-entity recognition batch_69abc5ddf00081909acb47cbd9a5f20e completed March 7, 2026, 6:29 a.m.
NED1 Entity disambiguation (via context triple) batch_69aef08a105081908455f482c6b2a880 completed March 9, 2026, 4:08 p.m.
Created at: March 4, 2026, 7:49 p.m.