Triple

T5044546
Position Surface form Disambiguated ID Type / Status
Subject Bon Voyage, Mr. President E113628 entity
Predicate originalTitle P65 FINISHED
Object Buen viaje, señor presidente E113628 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: Buen viaje, señor presidente | Statement: [Bon Voyage, Mr. President, originalTitle, Buen viaje, señor presidente]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Buen viaje, señor presidente
Context triple: [Bon Voyage, Mr. President, originalTitle, Buen viaje, señor presidente]
  • A. Bon Voyage, Mr. President chosen
    "Bon Voyage, Mr. President" is a short story by Gabriel García Márquez that follows an exiled Caribbean dictator facing illness, nostalgia, and political ghosts while living in Geneva.
  • B. Señor Presidente
    Señor Presidente is the formal Spanish honorific used to address the sitting President of Mexico.
  • C. Mr. President
    "Mr. President" is the formal style of address used for the presiding officer of the Massachusetts Senate.
  • D. Mr. President
    "Mr. President" is the formal spoken address traditionally used for the sitting President of the United States.
  • E. Mr. President
    "Mr. President" is the formal style of address used for the head of state of Romania.
  • 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_69bd44391fc48190a311ce9c826c209b completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd73fd81788190b7799f519277119a completed March 20, 2026, 4:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69bea47e5ba0819088217a9ad3ce2b0a completed March 21, 2026, 2 p.m.
Created at: March 20, 2026, 1:37 p.m.