Triple

T18802444
Position Surface form Disambiguated ID Type / Status
Subject Fernando Tatís E459789 entity
Predicate name P16 FINISHED
Object Fernando Tatís 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: Fernando Tatís | Statement: [Fernando Tatís, name, Fernando Tatís]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fernando Tatís
Context triple: [Fernando Tatís, name, Fernando Tatís]
  • A. Fernando Tatís chosen
    Fernando Tatís is a former Major League Baseball third baseman from the Dominican Republic, best known for once hitting two grand slams in a single inning.
  • B. José Antonio Mestre
    José Antonio Mestre is a Spanish-born businessman best known as the maternal grandfather of Prince Louis of Luxembourg and a member of the extended Grand Ducal Family of Luxembourg.
  • C. Eusebio Poncela
    Eusebio Poncela is a Spanish actor best known internationally for his work in auteur cinema, particularly in collaboration with director Pedro Almodóvar.
  • D. Fernando Carro
    Fernando Carro is a Spanish sports executive best known for serving as the chief executive and chairman of German football club Bayer 04 Leverkusen.
  • E. Fernando Nunes
    Fernando Nunes is a person notable enough to be recognized as a significant bearer of the surname Nunes.
  • 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_69d8d398c7d4819091cb2f7e48948aeb completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5a02400208190b1d84e2b0640df08 completed April 20, 2026, 3:40 a.m.
Created at: April 10, 2026, 11:53 a.m.