Triple

T3281193
Position Surface form Disambiguated ID Type / Status
Subject Another Country E68874 entity
Predicate hasCharacter P2308 FINISHED
Object Leona E245330 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: Leona | Statement: [Another Country, hasCharacter, Leona]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Leona
Context triple: [Another Country, hasCharacter, Leona]
  • A. Leona chosen
    Leona is a feminine given name used in various cultures, often derived from the Latin word for "lion."
  • B. Katarina
    Katarina is a feminine given name, commonly used in various European cultures, that is a variant of the name Catherine.
  • C. Tristana
    Tristana is a 1970 Spanish drama film directed by Luis Buñuel, known for its exploration of power, morality, and desire through the story of a young woman and her older guardian.
  • D. Liliana
    Liliana is a feminine given name, often considered a more elaborate or romantic variant of Lily, used in various cultures around the world.
  • E. Jinx
    Jinx is a Marvel Comics supervillain and member of the Hellfire Club’s Inner Circle, often associated with the mutant hunter Nimrod.
  • 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_69ad859c463481909ca4be267336c290 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb032d76c81909c568a4e56d12ce9 completed March 8, 2026, 5:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69b2e851d2bc8190ba887cd1c81c880d completed March 12, 2026, 4:22 p.m.
Created at: March 8, 2026, 3:10 p.m.