Triple

T21484705
Position Surface form Disambiguated ID Type / Status
Subject Guilielmus Amesius E530086 entity
Predicate workLocation P7 FINISHED
Object Friesland NE NERFINISHED

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: [Guilielmus Amesius, workLocation, Friesland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Friesland
Context triple: [Guilielmus Amesius, workLocation, 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. West-Friesland
    West-Friesland is a historical region in the northwest of the Netherlands known for its distinctive cultural identity, traditional landscapes, and old trading towns.
  • D. Drenthe, Netherlands
    Drenthe, Netherlands is a rural northeastern Dutch province known for its prehistoric dolmen tombs, extensive nature reserves, and quiet agricultural landscapes.
  • E. Kennemerland
    Kennemerland is a coastal historical region in the northwest of the Netherlands, known for its dunes, beaches, and old trading towns.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c45acc3881908e38d3f28964152b completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69e9ea365a8481909635f614b23e751f completed April 23, 2026, 9:45 a.m.
Created at: April 16, 2026, 6:21 p.m.