Triple

T9854818
Position Surface form Disambiguated ID Type / Status
Subject Weeds E239556 entity
Predicate starring P1507 FINISHED
Object Guillermo Díaz E463186 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: Guillermo Díaz | Statement: [Weeds, starring, Guillermo Díaz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Guillermo Díaz
Context triple: [Weeds, starring, Guillermo Díaz]
  • A. Guillermo Díaz chosen
    Guillermo Díaz is an American actor best known for his comedic and character roles in film and television, including his breakout performance in the stoner comedy "Half Baked."
  • B. Julio Díaz
    Julio Díaz is a Mexican former professional boxer and two-time IBF lightweight world champion known for his technical skill and resilience in the ring.
  • C. Gerardo González
    Gerardo González, better known by his ring name Kid Gavilán, was a renowned Cuban professional boxer and world welterweight champion famed for his flashy style and "bolo punch."
  • D. Guillermo Pulido
    Guillermo Pulido is a notable individual whose surname, Pulido, is recognized as being borne by him.
  • E. Miguel Ordóñez
    Miguel Ordóñez is an illustrator known for his playful, minimalist artwork in children’s books and other visual storytelling projects.
  • 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_69ca84e4fdc08190a624425bcef98665 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb3960fb481909c90d6d6cafc6222 completed April 2, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69e215ac56248190a75ad5ceb8152d5a completed April 17, 2026, 11:12 a.m.
Created at: March 30, 2026, 8:34 p.m.