Triple

T21131987
Position Surface form Disambiguated ID Type / Status
Subject municipality of Oss E520709 entity
Predicate contains P35 FINISHED
Object Oijen 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: Oijen | Statement: [municipality of Oss, contains, Oijen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oijen
Context triple: [municipality of Oss, contains, Oijen]
  • A. Oijen chosen
    Oijen is a village in the Dutch province of North Brabant that forms part of the municipality of Oss.
  • B. Kunoy
    Kunoy is a small, mountainous island in the Faroe Islands known for its dramatic cliffs, sparse population, and traditional fishing villages.
  • C. Watanobbi
    Watanobbi is a residential suburb on the Central Coast of New South Wales, Australia, known for its family-friendly atmosphere and proximity to major regional centres.
  • D. Оять
    Оять — река на северо-западе России, протекающая по территории Ленинградской и Вологодской областей и известная как значимый водный путь региона.
  • E. Omura
    Omura is a coastal city in western Japan known for its proximity to Nagasaki, Omura Bay, and its regional industrial and transportation hubs.
  • 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.