Triple

T8376625
Position Surface form Disambiguated ID Type / Status
Subject Cristina Fernández de Kirchner E197592 entity
Predicate givenName P17 FINISHED
Object Cristina E686863 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: [Cristina Fernández de Kirchner, givenName, Cristina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cristina
Context triple: [Cristina Fernández de Kirchner, givenName, Cristina]
  • A. Cristina
    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. Cristina
    Cristina is the wife of Brazilian basketball legend Oscar Schmidt.
  • D. Cristina chosen
    Cristina is a fictional cardiothoracic surgeon from the television series "Grey's Anatomy," known for her ambition, skill, and emotionally complex personality.
  • E. Cayetana
    Cayetana is the given name of Cayetana Fitz-James Stuart, the 18th Duchess of Alba, a prominent Spanish aristocrat known for holding a record number of noble titles.
  • 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_69ca82f64c188190af4e1608036b865d completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb80c094908190afe9cc54ce4f4d58 completed March 31, 2026, 8:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69cde7f19ba08190a08cf5aea522c021 completed April 2, 2026, 3:52 a.m.
Created at: March 30, 2026, 6:01 p.m.