Triple

T21281107
Position Surface form Disambiguated ID Type / Status
Subject Canto V E524524 entity
Predicate featuresCharacter P626 FINISHED
Object Ludmila 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: Ludmila | Statement: [Canto V, featuresCharacter, Ludmila]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ludmila
Context triple: [Canto V, featuresCharacter, Ludmila]
  • A. Ludmila chosen
    Ludmila is the heroine of Alexander Pushkin’s narrative poem "Ruslan and Ludmila," known as a beautiful Kievan princess whose abduction sets the story’s adventurous plot in motion.
  • B. Lyudmila
    Lyudmila is a Russian linguist and the former First Lady of Russia, known for being the ex-wife of President Vladimir Putin.
  • C. Lyudmila
    Lyudmila is a common Russian female given name, notably borne by figures such as Soviet World War II sniper Lyudmila Pavlichenko.
  • D. Ludmilla
    Ludmilla is a coastal suburb of Darwin in Australia's Northern Territory, known for its residential areas and proximity to Fannie Bay.
  • E. Galina
    Galina is a feminine given name of Slavic origin, commonly used in Russia and other Eastern European countries.
  • 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.