Triple

T9530289
Position Surface form Disambiguated ID Type / Status
Subject RusLine E229872 entity
Predicate focusCity P164 FINISHED
Object Perm E129564 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: Perm | Statement: [RusLine, focusCity, Perm]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Perm
Context triple: [RusLine, focusCity, Perm]
  • A. 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.
  • B. Permet
    Permet is a small town in southern Albania known for its scenic location along the Vjosa River, thermal springs, and surrounding mountainous landscapes.
  • C. Per
    Per is a Scandinavian masculine given name, commonly used in Norway, Sweden, and Denmark as a form of Peter.
  • D. Perm Sec
    Perm Sec is the common abbreviation for a Permanent Secretary, the most senior civil servant in a UK government department responsible for its day-to-day management and advising ministers.
  • E. Prem
    Prem is an Indian given name commonly used for males, derived from Sanskrit and meaning "love" or "affection."
  • 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_69ca8479934c81908006d0e6e970ae05 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd98b2de3081909be70d9ab187dce6 completed April 1, 2026, 10:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69d14c38a3848190ab3561f70497c9eb completed April 4, 2026, 5:36 p.m.
Created at: March 30, 2026, 8 p.m.