Triple

T12264095
Position Surface form Disambiguated ID Type / Status
Subject Pepita Tudó E292297 entity
Predicate givenName P17 FINISHED
Object Pepita E859472 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: Pepita | Statement: [Pepita Tudó, givenName, Pepita]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pepita
Context triple: [Pepita Tudó, givenName, Pepita]
  • A. Pepita chosen
    Pepita is the nickname of Spanish soprano Pepita Embil, known for her performances in zarzuela and as the mother of renowned tenor Plácido Domingo.
  • B. Pepita
    Pepita is a shy, self-effacing orphan and ward of the Abbess in Thornton Wilder’s novel "The Bridge of San Luis Rey," whose inner strength and unspoken love make her one of the book’s most poignant figures.
  • C. Pilar
    Pilar is a Spanish feminine given name, often associated with religious devotion to Our Lady of the Pillar and traditionally used in Spain and Spanish-speaking countries.
  • D. Pilar
    Pilar is a strong-willed, perceptive Spanish guerrilla fighter who plays a central role in Ernest Hemingway’s novel "For Whom the Bell Tolls."
  • E. Pilar
    Pilar is a riverside city in southwestern Paraguay known for its colonial architecture, river port activities, and proximity to the border with Argentina.
  • 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_69d6ab6856488190b5d31178d5015f8e completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91cdc42988190b4e2a6591a6f919d completed April 10, 2026, 3:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69f60ac3ce008190856a917c2c75862a completed May 2, 2026, 2:31 p.m.
Created at: April 8, 2026, 9:52 p.m.