Triple

T14675109
Position Surface form Disambiguated ID Type / Status
Subject Dutch Gothic E344615 entity
Predicate geographicDistribution P2178 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: [Dutch Gothic, geographicDistribution, Friesland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Friesland
Context triple: [Dutch Gothic, geographicDistribution, 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 (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_69d822e283fc8190a0e4c235cf880052 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb5666e648190b5faa07076f497b8 completed April 14, 2026, 9:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe0cde041081908ae2f2c75a9d5eb2 completed May 8, 2026, 4:18 p.m.
Created at: April 10, 2026, 1:27 a.m.