Triple

T9747091
Position Surface form Disambiguated ID Type / Status
Subject Fyodor E236337 entity
Predicate hasDiminutive P456 FINISHED
Object Fedyusha E236337 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: Fedyusha | Statement: [Fyodor, hasDiminutive, Fedyusha]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fedyusha
Context triple: [Fyodor, hasDiminutive, Fedyusha]
  • A. Olyusha
    Olyusha is a Russian diminutive form of the female given name Olga, typically used as an affectionate nickname.
  • B. Vasily
    Vasily is a masculine given name of Slavic origin, commonly used in Russian-speaking countries.
  • C. Fyodor chosen
    Fyodor is a masculine given name of Russian origin, most famously borne by the novelist Fyodor Dostoevsky.
  • D. Yuri of Uglich
    Yuri of Uglich was a Russian prince of the early 16th century, known as a younger son of Grand Prince Vasili III and a member of the ruling Rurikid dynasty.
  • E. Foma Gordeyev
    Foma Gordeyev is a novel by Russian writer Maksim Gorky that portrays the moral and spiritual decline of a wealthy merchant’s son amid the social tensions of late 19th-century Russia.
  • 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_69ca84d3e24481908a476e2231123cf9 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9f677830819096d388b9c798ecd5 completed April 1, 2026, 10:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69d36947145c8190a0137efdad0bca91 completed April 6, 2026, 8:05 a.m.
Created at: March 30, 2026, 8:23 p.m.