Triple

T4169557
Position Surface form Disambiguated ID Type / Status
Subject Ede E84526 entity
Predicate hasNeighbouringMunicipality P224 FINISHED
Object Wageningen E466289 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: Wageningen | Statement: [Ede, hasNeighbouringMunicipality, Wageningen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wageningen
Context triple: [Ede, hasNeighbouringMunicipality, Wageningen]
  • A. Wageningen chosen
    Wageningen is a Dutch town historically significant as the site where German forces in the Netherlands formally surrendered at the end of World War II.
  • B. Utrecht
    Utrecht is a historic city and province in the central Netherlands, known for its medieval old town, canals, and role as a religious and cultural center.
  • C. Nijmegen
    Nijmegen is a historic Dutch city near the German border that played a crucial strategic role during World War II, particularly in the Allied advance in 1944.
  • D. Hoogeveen
    Hoogeveen is a town and municipality in the northeastern Netherlands known for its historical peat colonies and location in the province of Drenthe.
  • E. Leiden
    Leiden is a historic Dutch city in South Holland known for its prestigious university, rich cultural heritage, and well-preserved canals and old town.
  • 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_69aed932cab48190b80ffe35f7029ae1 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af02c730b081908b19e6a4aea1549b completed March 9, 2026, 5:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69d2cae488708190823b1e9c07ad2e48 completed April 5, 2026, 8:49 p.m.
Created at: March 9, 2026, 3:44 p.m.