Triple

T22707176
Position Surface form Disambiguated ID Type / Status
Subject Yuriatin E561486 entity
Predicate modeledOn P7125 FINISHED
Object Perm (disputed/approximate literary model) 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: Perm (disputed/approximate literary model) | Statement: [Yuriatin, modeledOn, Perm (disputed/approximate literary model)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Perm (disputed/approximate literary model)
Context triple: [Yuriatin, modeledOn, Perm (disputed/approximate literary model)]
  • A. Permet
    Permet is a small town in southern Albania known for its scenic location along the Vjosa River, thermal springs, and surrounding mountainous landscapes.
  • B. Perm chosen
    Perm is a major industrial and cultural city in the Ural region of Russia, situated on the Kama River and historically significant as a gateway between European and Asian Russia.
  • C. Perlisian
    A Perlisian is a person from Perlis, the smallest and northernmost state in Peninsular Malaysia.
  • D. PERM
    PERM is the U.S. Department of Labor’s permanent labor certification process that employers must complete to hire foreign workers for certain employment-based green card categories.
  • E. Pemper
    Pemper is a surname most notably associated with Mietek Pemper, a Holocaust survivor who helped compile Oskar Schindler’s list.
  • 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_69e2454f1348819088d83f420925a5c1 completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f178cff7588190a40c8cef0f3cd44a completed April 29, 2026, 3:19 a.m.
Created at: April 17, 2026, 3:17 p.m.