Triple

T21195131
Position Surface form Disambiguated ID Type / Status
Subject Canto III E522306 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 III, featuresCharacter, Ludmila]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ludmila
Context triple: [Canto III, 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 common Russian female given name, notably borne by figures such as Soviet World War II sniper Lyudmila Pavlichenko.
  • C. Lyudmila
    Lyudmila is a Russian linguist and the former First Lady of Russia, known for being the ex-wife of President Vladimir Putin.
  • 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_69e0b51061388190aa03f19700d3ef04 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e7333aa0fc81909b17eb6a26f389ec completed April 21, 2026, 8:20 a.m.
Created at: April 16, 2026, 3:08 p.m.