Triple

T21443909
Position Surface form Disambiguated ID Type / Status
Subject San Dominick E529018 entity
Predicate captainCharacter P31052 FINISHED
Object Don Benito Cereno 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: Don Benito Cereno | Statement: [San Dominick, captainCharacter, Don Benito Cereno]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Don Benito Cereno
Context triple: [San Dominick, captainCharacter, Don Benito Cereno]
  • A. Benito Cereno chosen
    Benito Cereno is a novella by Herman Melville that explores themes of slavery, power, and deception through the mysterious encounter between an American captain and a Spanish slave ship.
  • B. Maturín
    Maturín is a major city in eastern Venezuela known as an important commercial and oil-industry center.
  • C. Compay Segundo
    Compay Segundo was a renowned Cuban guitarist, singer, and songwriter best known as a leading figure of the Buena Vista Social Club and a symbol of traditional Cuban son music.
  • D. Eustaquio
    Eustaquio is a masculine given name of Spanish origin, historically borne by several notable figures in Latin America.
  • E. Pintel
    Pintel is a bumbling yet resourceful pirate best known as a comic-relief crewman aboard the Black Pearl in the Pirates of the Caribbean film series.
  • 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_69e0c4569fa081908101baa24f8745db completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69e8b7055d148190ae3b52e10abd8fd2 completed April 22, 2026, 11:54 a.m.
Created at: April 16, 2026, 6:05 p.m.