Triple

T10511036
Position Surface form Disambiguated ID Type / Status
Subject Doug Sahm E247914 entity
Predicate associatedAct P37 FINISHED
Object Flaco Jiménez E132156 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: Flaco Jiménez | Statement: [Doug Sahm, associatedAct, Flaco Jiménez]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Flaco Jiménez
Context triple: [Doug Sahm, associatedAct, Flaco Jiménez]
  • A. Flaco Jiménez chosen
    Flaco Jiménez is a renowned Tex-Mex and conjunto accordionist celebrated for his influential collaborations across country, rock, and Latin music.
  • B. Omar Bravo
    Omar Bravo is a Mexican former professional footballer best known as a prolific forward for C.D. Guadalajara and the Mexico national team.
  • C. Pedro Muzquiz
    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.
  • D. Jesus Tarango
    Jesus Tarango is a Native American tribal leader who serves as the chairperson of the Wilton Rancheria in California.
  • E. Salvador Magaña
    Salvador Magaña is a person notable enough to be recognized as a prominent bearer of the surname Magaña.
  • 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_69d381c4aa948190942e1d803143fb0e completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d509b542088190868531f84deaf9e4 completed April 7, 2026, 1:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69d933e4ae048190be51a02c571fab8b completed April 10, 2026, 5:31 p.m.
Created at: April 6, 2026, 12:27 p.m.