Triple

T15319372
Position Surface form Disambiguated ID Type / Status
Subject Leende E366246 entity
Predicate locatedNear P294 FINISHED
Object Geldrop E505528 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: Geldrop | Statement: [Leende, locatedNear, Geldrop]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Geldrop
Context triple: [Leende, locatedNear, Geldrop]
  • A. Geldrop-Mierlo chosen
    Geldrop-Mierlo is a municipality in the province of North Brabant in the southern Netherlands, known for its residential communities and proximity to the city of Eindhoven.
  • B. Diksmuide
    Diksmuide is a historic town in western Belgium known for its World War I battlefields and memorials, particularly the Yser Tower.
  • C. Groesbeek
    Groesbeek is a village in the Dutch province of Gelderland, known for its hilly landscape, World War II history, and wine production.
  • D. Molenschot
    Molenschot is a small village in the Dutch province of North Brabant, known for its rural character and traditional local community.
  • E. Heemskerk
    Heemskerk is a town and municipality in North Holland in the Netherlands, known for its coastal dunes, historic estates, and residential 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_69d85a121520819093dcce999fdefe1a completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03dd356b881908f054b64eee6a371 completed April 16, 2026, 1:39 a.m.
NED1 Entity disambiguation (via context triple) batch_69fef8a9085881909904152c32b0fed1 completed May 9, 2026, 9:04 a.m.
Created at: April 10, 2026, 3:16 a.m.