Triple

T21131990
Position Surface form Disambiguated ID Type / Status
Subject municipality of Oss E520709 entity
Predicate contains P35 FINISHED
Object Keent NE NERFINISHED

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: Keent | Statement: [municipality of Oss, contains, Keent]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Keent
Context triple: [municipality of Oss, contains, Keent]
  • A. Keent chosen
    Keent is a small rural hamlet in the Dutch province of North Brabant, known for its riverine landscape and nature restoration areas along the Maas.
  • B. Keen
    Keen is a surname of English origin borne by various notable individuals across fields such as acting, sports, and academia.
  • C. Keener
    Keener is a surname most prominently associated with American actress Catherine Keener, known for her acclaimed roles in independent and mainstream films.
  • D. Kee
    Kee is a pivotal character in the dystopian film "Children of Men," a miraculously pregnant refugee whose unborn child represents humanity’s last hope for survival.
  • E. Kesten
    Kesten is a surname most notably associated with Harry Kesten, a prominent mathematician known for his work in probability theory.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b50b53048190ae34e8abbe3c5ada completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e7235668e081909bd810016ba2dd8e completed April 21, 2026, 7:12 a.m.
Created at: April 16, 2026, 2:56 p.m.