Triple

T14098046
Position Surface form Disambiguated ID Type / Status
Subject Sedova E339305 entity
Predicate derivedFrom P909 FINISHED
Object Sedov E535375 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: Sedov | Statement: [Sedova, derivedFrom, Sedov]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sedov
Context triple: [Sedova, derivedFrom, Sedov]
  • A. Sedov chosen
    Sedov is a Russian surname most notably associated with Lev Sedov, the revolutionary son of Leon Trotsky.
  • B. Kozhedub
    Kozhedub is a Slavic surname most famously borne by Ivan Kozhedub, a highly decorated Soviet World War II fighter ace.
  • C. Saha
    Saha is a surname most notably associated with Indian astrophysicist Meghnad Saha, known for the Saha ionization equation in stellar astrophysics.
  • D. Saha
    Saha is a small town in the Ambala district of the northern Indian state of Haryana, known primarily as a local commercial and transport hub for surrounding rural areas.
  • E. Slobodskoy
    Slobodskoy is a historic town in Kirov Oblast, Russia, known as the birthplace of the writer Alexander Grin.
  • 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_69d81c69b5c8819094aa1abf18302908 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de5fb926288190a7f0f50d1d585d76 completed April 14, 2026, 3:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcd0adfc28819097a1bfd56739c286 completed May 7, 2026, 5:49 p.m.
Created at: April 9, 2026, 10:22 p.m.