Triple

T6520291
Position Surface form Disambiguated ID Type / Status
Subject Cup’ig dialect E148361 entity
Predicate hasLoanwordsFrom P506 FINISHED
Object Russian E3584 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: Russian | Statement: [Cup’ig dialect, hasLoanwordsFrom, Russian]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Russian
Context triple: [Cup’ig dialect, hasLoanwordsFrom, Russian]
  • A. Russo
    Russo is an Italian surname commonly used as a variant of Rossi, often associated with people of Italian heritage.
  • B. Rus
    Rus was a medieval East Slavic cultural and political realm that laid the foundations for the modern nations of Russia, Ukraine, and Belarus.
  • C. Russin
    Russin is a small wine-producing municipality and village located in the canton of Geneva in southwestern Switzerland.
  • D. Russi
    Russi is a small historic town and municipality in the Emilia-Romagna region of northern Italy, known for its Roman archaeological remains and agricultural surroundings.
  • E. Russian language chosen
    Russian is an East Slavic language spoken primarily in Russia and neighboring countries, serving as one of the world's major languages in politics, science, and culture.
  • 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_69c687e68e748190baceb9298f32d3ed completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6ad92c624819086dbb12b4f6b78d3 completed March 27, 2026, 4:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6e41434108190b6c329544764dd2c completed March 27, 2026, 8:09 p.m.
Created at: March 27, 2026, 1:45 p.m.