Triple

T11626679
Position Surface form Disambiguated ID Type / Status
Subject County of Guelders E276287 entity
Predicate capital P234 FINISHED
Object Geldern E527096 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: Geldern | Statement: [County of Guelders, capital, Geldern]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Geldern
Context triple: [County of Guelders, capital, Geldern]
  • A. Geldern chosen
    Geldern is a historic town in western Germany, notable as the namesake and former center of the medieval Duchy of Guelders.
  • B. Zutphen
    Zutphen is a historic city in the eastern Netherlands known for its well-preserved medieval center and location along the river IJssel.
  • C. Zundert
    Zundert is a municipality and town in the southern Netherlands, known as the birthplace of painter Vincent van Gogh and for hosting one of the world's largest flower parades.
  • D. Culemborg
    Culemborg is a historic town in the Dutch province of Gelderland, known for its medieval center and role in the early Dutch colonial era.
  • E. Woerden
    Woerden is a historic Dutch city and municipality in the central Netherlands, known for its medieval fortifications and traditional cheese market.
  • 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_69d6aafa51148190ab84940694c00235 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a1259cd08190a75eeacb5e39b858 completed April 10, 2026, 7:05 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00c78f36d88190a39f407c5d8dbc0d completed May 10, 2026, 5:59 p.m.
Created at: April 8, 2026, 9:39 p.m.