Triple

T12516361
Position Surface form Disambiguated ID Type / Status
Subject lzip E299199 entity
Predicate maintainer P2962 FINISHED
Object Antonio Diaz Diaz E1077906 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: Antonio Diaz Diaz | Statement: [lzip, maintainer, Antonio Diaz Diaz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Antonio Diaz Diaz
Context triple: [lzip, maintainer, Antonio Diaz Diaz]
  • A. Antonio Diaz Diaz chosen
    Antonio Diaz Diaz is a software developer best known for creating data compression tools such as lzip.
  • B. Guillermo Díaz
    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."
  • C. Antonio Rivera Rodríguez
    Antonio Rivera Rodríguez was a notable Puerto Rican figure after whom the main airport on the island of Vieques is named.
  • D. 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.
  • E. Antonio Reynoso
    Antonio Reynoso is an American politician and community advocate who serves as the Borough President of Brooklyn, New York City.
  • 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_69d6ada5cdd48190860d9ce30aff69be completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d9541f80148190976d1d912fe155d0 completed April 10, 2026, 7:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcd082fe64819088a270f18190b172 completed May 7, 2026, 5:48 p.m.
Created at: April 8, 2026, 9:57 p.m.