Triple

T9871852
Position Surface form Disambiguated ID Type / Status
Subject Sanchica E239974 entity
Predicate relative P37 FINISHED
Object Teresa Panza E256412 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: Teresa Panza | Statement: [Sanchica, relative, Teresa Panza]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Teresa Panza
Context triple: [Sanchica, relative, Teresa Panza]
  • A. Teresa Panza chosen
    Teresa Panza is a fictional character in Miguel de Cervantes' "Don Quixote," known as the practical and down-to-earth wife of the squire Sancho Panza.
  • B. Teresa Bocciardo
    Teresa Bocciardo was the mother of the famed Italian violin virtuoso and composer Niccolò Paganini.
  • C. Teresa Pomar
    Teresa Pomar was a prominent Mexican researcher, curator, and promoter of folk and popular art, recognized for her extensive work preserving and documenting Mexico’s artisanal traditions.
  • D. Teresa Barba
    Teresa Barba was the wife and close companion of renowned Catalan painter and sculptor Antoni Tàpies.
  • E. Teresa Viola
    Teresa Viola is an American businesswoman and philanthropist known for her involvement in charitable initiatives and as the wife of billionaire businessman and NHL team owner Vincent Viola.
  • 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_69ca84e8a0788190b9061811d50fd554 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb3f5cc948190b03186b867c92229 completed April 2, 2026, 12:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69d23d09790c8190be161d2dbef2e881 completed April 5, 2026, 10:44 a.m.
Created at: March 30, 2026, 8:36 p.m.