Triple

T23432328
Position Surface form Disambiguated ID Type / Status
Subject Volga-Ural region E563364 entity
Predicate contains P35 FINISHED
Object Mari El 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: Mari El | Statement: [Volga-Ural region, contains, Mari El]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mari El
Context triple: [Volga-Ural region, contains, Mari El]
  • A. Mari El chosen
    Mari El is a federal republic of Russia located along the Volga River, known for its indigenous Mari people and their Finno-Ugric cultural and linguistic heritage.
  • B. Mia Sara
    Mia Sara is an American actress best known for her role as Sloane Peterson in the 1986 teen comedy film "Ferris Bueller's Day Off."
  • C. Loana
    Loana is a prehistoric cavewoman character from the 1940 fantasy film "One Million B.C.," known for her role in the story’s depiction of early human life and tribal conflict.
  • D. Maya Gallo
    Maya Gallo is a smart, idealistic journalist and the daughter of Blush magazine’s publisher on the sitcom "Just Shoot Me!", often serving as the show’s moral center amid its fashion-world chaos.
  • E. Mira Calix
    Mira Calix was an innovative South African-born, UK-based electronic composer and sound artist known for blending experimental electronics with classical instrumentation and multimedia installations.
  • 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_69e24553980c8190bb66a2ae0bdab125 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f1a5d920548190904f80c7c40cba06 completed April 29, 2026, 6:31 a.m.
Created at: April 17, 2026, 5:49 p.m.