Triple

T2279786
Position Surface form Disambiguated ID Type / Status
Subject Mari El Republic E51254 entity
Predicate largestCity P235 FINISHED
Object Yoshkar-Ola E271616 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: Yoshkar-Ola | Statement: [Mari El Republic, largestCity, Yoshkar-Ola]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yoshkar-Ola
Context triple: [Mari El Republic, largestCity, Yoshkar-Ola]
  • A. Yoshkar-Ola chosen
    Yoshkar-Ola is a city in central Russia that serves as the administrative, cultural, and economic center of the Mari El Republic.
  • B. Nukus
    Nukus is the capital of the autonomous Republic of Karakalpakstan in western Uzbekistan, known for its remote desert location and the renowned Nukus Museum of Art.
  • C. Karaganda
    Karaganda is a large industrial city in central Kazakhstan known for its coal mining industry and Soviet-era history.
  • D. Kizlyar
    Kizlyar is a town in the Republic of Dagestan, Russia, known historically as a frontier settlement and trading center in the North Caucasus region.
  • E. Kaspiysk
    Kaspiysk is a coastal city on the Caspian Sea in the Republic of Dagestan, Russia, known for its industrial base and strategic naval facilities.
  • 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_69a88b08e4308190bdac9aebcca1c91a completed March 4, 2026, 7:42 p.m.
NER Named-entity recognition batch_69abc2194150819083156e4dcd45a423 completed March 7, 2026, 6:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69af2b6475948190816531b026c7930c completed March 9, 2026, 8:19 p.m.
Created at: March 4, 2026, 7:48 p.m.