Triple

T15131132
Position Surface form Disambiguated ID Type / Status
Subject Driewegen E361421 entity
Predicate locatedIn P40 FINISHED
Object Borsele E73295 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: Borsele | Statement: [Driewegen, locatedIn, Borsele]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Borsele
Context triple: [Driewegen, locatedIn, Borsele]
  • A. Borsele chosen
    Borsele is a municipality in the Dutch province of Zeeland, known for its rural landscape, villages, and the nearby Borssele nuclear power plant.
  • B. Borssum
    Borssum is a district of the seaport city of Emden in Lower Saxony, Germany, known primarily as a residential area with local amenities.
  • C. Boskoop
    Boskoop is a Dutch town historically renowned as a major center of tree and nursery cultivation.
  • D. Borgloon
    Borgloon is a historic town in the Belgian province of Limburg that once served as the political and administrative center of the medieval County of Loon.
  • E. Zoersel
    Zoersel is a municipality in the Belgian province of Antwerp, known for its green residential character and wooded surroundings.
  • 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_69d85a06450081909c5a14ea9851a15e completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e005b194748190801e3956bf2429d4 completed April 15, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69fed321d6108190a30b32f176e6d4dc completed May 9, 2026, 6:24 a.m.
Created at: April 10, 2026, 3:06 a.m.