Triple

T22328465
Position Surface form Disambiguated ID Type / Status
Subject Charlotte Smith E551962 entity
Predicate notableWork P4 FINISHED
Object Celestina 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: Celestina | Statement: [Charlotte Smith, notableWork, Celestina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Celestina
Context triple: [Charlotte Smith, notableWork, Celestina]
  • A. Celestina
    Celestina is a character in Carlos Fuentes’s novel "Terra Nostra," contributing to its complex, multi-layered exploration of Spanish and Latin American history and myth.
  • B. La Celestina chosen
    La Celestina is a seminal late 15th-century Spanish tragicomedy, often considered a precursor to the modern novel and a cornerstone of Spanish Renaissance literature.
  • C. La Rosaura
    La Rosaura is an opera by Italian Baroque composer Alessandro Scarlatti, exemplifying his influential contribution to early 18th-century opera.
  • D. Doña Eloisa
    Doña Eloisa is a minor character in the television series "Prison Break," known as the aunt of Fernando Sucre.
  • E. Fausto
    Fausto is an Italian given name most notably associated with the Renaissance theologian and thinker Fausto Sozzini.
  • 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_69e11e482f788190b78d1588fc26d606 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15769fdb48190b84e0c019ab63579 completed April 29, 2026, 12:57 a.m.
Created at: April 16, 2026, 8:43 p.m.