Triple

T3554457
Position Surface form Disambiguated ID Type / Status
Subject Christina E75185 entity
Predicate hasVariant P455 FINISHED
Object Cristina E316600 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: Cristina | Statement: [Christina, hasVariant, Cristina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cristina
Context triple: [Christina, hasVariant, Cristina]
  • A. Cristina chosen
    Cristina is one of the two free-spirited American women at the center of Woody Allen’s romantic drama film "Vicky Cristina Barcelona."
  • B. Cristina
    Cristina is a Spanish infanta and member of the Spanish royal family, known as the daughter of former King Juan Carlos I and Queen Sofía.
  • C. Maria Cerezo
    Maria Cerezo was the wife of Italian explorer and cartographer Amerigo Vespucci, after whom the Americas are named.
  • D. Romina
    Romina is an Italian-American actress and singer best known as half of the pop duo Al Bano & Romina Power.
  • E. Cristina Banegas
    Cristina Banegas is an acclaimed Argentine actress and director recognized internationally for her powerful performances in film, television, and theater.
  • 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_69ad85d33c6c819081d5ac1df13b5680 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc05549d88190acdebdd542ea1a67 completed March 8, 2026, 6:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69b402e41b8c8190b6221725c7a84532 completed March 13, 2026, 12:28 p.m.
Created at: March 8, 2026, 3:20 p.m.