Triple

T21742265
Position Surface form Disambiguated ID Type / Status
Subject SE121 Uppsala län E536686 entity
Predicate statisticalSystem P49001 FINISHED
Object NUTS 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: NUTS | Statement: [SE121 Uppsala län, statisticalSystem, NUTS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: NUTS
Context triple: [SE121 Uppsala län, statisticalSystem, NUTS]
  • A. NUTS chosen
    NUTS is the Nomenclature of Territorial Units for Statistics, a hierarchical system used to divide countries into regions for the collection, development, and harmonization of regional statistics.
  • B. NUTN
    NUTN is the abbreviation for the National University of Tainan, a public university in Tainan, Taiwan known for its teacher education and humanities programs.
  • C. NUT
    NUT is the commonly used abbreviation for Nagaoka University of Technology, a Japanese national university specializing in engineering and technology.
  • D. Nucet
    Nucet is a small town in northwestern Romania known for its location in the Apuseni Mountains region of Bihor County.
  • E. Nutt
    Nutt is a surname most notably associated with David Nutt, a British neuropsychopharmacologist known for his research on the effects of drugs on the brain and for advising on drug policy.
  • 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_69e0c46df5448190b4322127ffc4c690 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69f01a7322348190b2145fa922c480ed completed April 28, 2026, 2:24 a.m.
Created at: April 16, 2026, 6:49 p.m.