Triple

T21281111
Position Surface form Disambiguated ID Type / Status
Subject Canto V E524524 entity
Predicate featuresCharacter P626 FINISHED
Object Ratmir NE NERFINISHED

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: Ratmir | Statement: [Canto V, featuresCharacter, Ratmir]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ratmir
Context triple: [Canto V, featuresCharacter, Ratmir]
  • A. Ratmir chosen
    Ratmir is a Tatar prince who appears as a gallant yet ultimately reformed seducer in Alexander Pushkin’s narrative poem "Ruslan and Ludmila."
  • B. Arseny
    Arseny is a masculine given name of Russian origin, historically borne by several notable figures in literature, art, and public life.
  • C. Gerasimov
    Gerasimov is a Russian surname borne by various notable figures in fields such as the military, arts, and sciences.
  • D. Mikhaylovich
    Mikhaylovich is a Russian patronymic name indicating that a person is the son of someone named Mikhail.
  • E. Pavel Batov
    Pavel Batov was a distinguished Soviet general who commanded key formations on the Eastern Front during World War II and later held senior military and political posts in the USSR.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b5171f6c8190a5d57201ede73811 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e736d186988190a5b16fcb669ece9f completed April 21, 2026, 8:35 a.m.
Created at: April 16, 2026, 4:02 p.m.