Triple

T714849
Position Surface form Disambiguated ID Type / Status
Subject Achterhooks E14290 entity
Predicate region P40 FINISHED
Object Achterhoek E128780 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: Achterhoek | Statement: [Achterhooks, region, Achterhoek]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Achterhoek
Context triple: [Achterhooks, region, Achterhoek]
  • A. Achterhoek chosen
    Achterhoek is a rural region in the eastern Netherlands known for its scenic landscapes, traditional farms, and distinctive local culture and dialect.
  • B. Westerkwartier
    Westerkwartier is a municipality in the Dutch province of Groningen, known for its rural landscapes, historic villages, and distinctive regional culture.
  • C. Oud-Beijerland
    Oud-Beijerland is a town in the western Netherlands known as one of the main population centers in the Hoeksche Waard region.
  • D. Uithoorn
    Uithoorn is a town and municipality in the province of North Holland in the Netherlands, situated along the Amstel River.
  • E. Salland
    Salland is a historical and rural region in the Dutch province of Overijssel, known for its scenic landscapes, small towns, and agricultural character.
  • 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_69a4934a36e081909e7abef98b898a4e completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a5738e04819082eac673b3b7c4c2 completed March 1, 2026, 8:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac598bddf88190afc565deec2357a1 completed March 7, 2026, 4:59 p.m.
Created at: March 1, 2026, 7:36 p.m.