Triple

T8960337
Position Surface form Disambiguated ID Type / Status
Subject Paola Núñez E213984 entity
Predicate birthName P65 FINISHED
Object Paola Núñez Rivas E213984 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: Paola Núñez Rivas | Statement: [Paola Núñez, birthName, Paola Núñez Rivas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paola Núñez Rivas
Context triple: [Paola Núñez, birthName, Paola Núñez Rivas]
  • A. Paola Núñez chosen
    Paola Núñez is a Mexican actress and producer known for her work in telenovelas and English-language television and film, including prominent roles in series like The Purge and the film Bad Boys for Life.
  • B. Mónica Naranjo
    Mónica Naranjo is a Spanish singer and songwriter known for her powerful vocal range and influential pop and dance music career since the 1990s.
  • C. María Valenzuela
    María Valenzuela is an Argentine actress known for her extensive work in television, film, and theater across several decades.
  • D. Nilsa Castro Espín
    Nilsa Castro Espín is a Cuban figure known primarily as the daughter of revolutionary leader Vilma Espín and Cuban president Raúl Castro.
  • E. Marivi Lorido García
    Marivi Lorido García is a film producer best known as the longtime wife of Cuban-American actor Andy García.
  • 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_69ca839cd6008190a1546a701a56710c completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc6746fbf88190aba658b4b9c2e4b0 completed April 1, 2026, 12:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69d0475435808190a80d82b6614b1308 completed April 3, 2026, 11:03 p.m.
Created at: March 30, 2026, 7 p.m.