Triple

T20128357
Position Surface form Disambiguated ID Type / Status
Subject Lorenzo Daza E490817 entity
Predicate child P120 FINISHED
Object Fermina Daza 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: Fermina Daza | Statement: [Lorenzo Daza, child, Fermina Daza]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fermina Daza
Context triple: [Lorenzo Daza, child, Fermina Daza]
  • A. Fermina Daza chosen
    Fermina Daza is a central character in Gabriel García Márquez’s novel "Love in the Time of Cholera," known for her complex romantic life and enduring, conflicted relationship with Florentino Ariza.
  • B. Pilar
    Pilar is the introspective female protagonist of Paulo Coelho’s novel "By the River Piedra I Sat Down and Wept," whose spiritual and emotional journey drives the story.
  • C. Pilar
    Pilar is a coastal town on Siargao Island in the Philippines, known for its fishing communities and access to popular surfing and eco-tourism spots.
  • D. Pilar
    Pilar is a municipality in the Philippine province of Abra, known for its rural highland landscapes and predominantly agricultural economy.
  • E. 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.
  • 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_69da62651a0c8190a3e05e95e056a66b completed April 11, 2026, 3:01 p.m.
NER Named-entity recognition batch_69e6675fe3d48190b0c20b483a951e68 completed April 20, 2026, 5:50 p.m.
Created at: April 11, 2026, 11:31 p.m.