Triple

T13706009
Position Surface form Disambiguated ID Type / Status
Subject Our Lady of Peñafrancia E328642 entity
Predicate languageVariantName P20733 FINISHED
Object Ina E878919 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: Ina | Statement: [Our Lady of Peñafrancia, languageVariantName, Ina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ina
Context triple: [Our Lady of Peñafrancia, languageVariantName, Ina]
  • A. Ina chosen
    Ina is a feminine given name that gained literary prominence through figures such as American poet Ina Coolbrith.
  • B. Ina Balin
    Ina Balin was an American actress best known for her work in film and television during the 1950s and 1960s, including a Golden Globe–winning performance in "From the Terrace."
  • C. Lidia
    Lidia Zamenhof was a Polish Esperantist, translator, and writer, known for promoting Esperanto and translating major literary works into the language.
  • D. Lidia
    Lidia is a central character in the Spanish television series "La verdad," around whom much of the mystery and drama of the plot revolves.
  • E. Melva
    Melva is a character in Richard Bruce Nugent’s modernist short story "Smoke, Lilies and Jade," which explores themes of race, sexuality, and artistic identity during the Harlem Renaissance.
  • 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_69d8076ff62081908a7bd79889edd7a0 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dcad17732c8190bbd0d73107711c99 completed April 13, 2026, 8:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69f79d50f34c8190ac5b4e09ab57baa9 completed May 3, 2026, 7:09 p.m.
Created at: April 9, 2026, 9:54 p.m.