Triple

T20086927
Position Surface form Disambiguated ID Type / Status
Subject Tita E496159 entity
Predicate inLoveWith P7325 FINISHED
Object Pedro Muzquiz 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: Pedro Muzquiz | Statement: [Tita, inLoveWith, Pedro Muzquiz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pedro Muzquiz
Context triple: [Tita, inLoveWith, Pedro Muzquiz]
  • A. Pedro Muzquiz chosen
    Pedro Muzquiz is the passionate yet conflicted love interest of Tita in Laura Esquivel’s novel "Like Water for Chocolate," whose forbidden romance drives much of the story’s emotional tension.
  • B. Roberto Muzquiz
    Roberto Muzquiz is the child of Rosaura De la Garza, a member of her immediate family.
  • C. Emilio Murguía
    Emilio Murguía is a notable individual bearing the Murguía surname, recognized for his contributions in his respective field.
  • D. José Gutiérrez
    José Gutiérrez was the architect responsible for designing the historic Hospicio Cabañas, a prominent neoclassical complex in Guadalajara, Mexico.
  • E. Lorenzo Benavides
    Lorenzo Benavides is a character in the Mexican film "El gallo de oro," involved in the dramatic world surrounding cockfighting and ambition.
  • 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_69da626eee3881909f3454986d4a6511 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e6655ba40c8190adea0e271a1249cf completed April 20, 2026, 5:41 p.m.
Created at: April 11, 2026, 11:12 p.m.