Triple

T11402411
Position Surface form Disambiguated ID Type / Status
Subject Maria Buynosova-Rostovskaya E270145 entity
Predicate region P40 FINISHED
Object Rus’ E158473 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: Rus’ | Statement: [Maria Buynosova-Rostovskaya, region, Rus’]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rus’
Context triple: [Maria Buynosova-Rostovskaya, region, Rus’]
  • A. Rus' chosen
    Rus' was a medieval East Slavic state that emerged in Eastern Europe and laid the foundations for the later Russian, Ukrainian, and Belarusian nations.
  • B. Rusko
    Rusko is a small municipality in southwestern Finland known for its rural character and proximity to the city of Turku.
  • C. Rusguniae
    Rusguniae was an important ancient coastal city in the Roman province of Mauretania Caesariensis, located in what is now northern Algeria.
  • D. Rusa
    Rusa is a genus of deer native to South and Southeast Asia, including species such as the Javan rusa and sambar.
  • E. Russas
    Russas is a municipality in the northeastern Brazilian state of Ceará, known for its agricultural activities and semi-arid climate.
  • 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_69d6aacdbc6c8190af6dc3d5f5d22836 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d80148e2048190a716b515d78efdd1 completed April 9, 2026, 7:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69e5d3470e208190aef43936bac2e4e9 completed April 20, 2026, 7:18 a.m.
Created at: April 8, 2026, 9:34 p.m.