Triple

T14191107
Position Surface form Disambiguated ID Type / Status
Subject Paid in Full (film) E351714 entity
Predicate castMember P1668 FINISHED
Object Esai Morales E393307 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: Esai Morales | Statement: [Paid in Full (film), castMember, Esai Morales]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Esai Morales
Context triple: [Paid in Full (film), castMember, Esai Morales]
  • A. Esai Morales chosen
    Esai Morales is an American actor known for his versatile roles in film and television, including prominent performances in series like NYPD Blue, Ozark, and Titans.
  • B. Robert Morales
    Robert Morales was an American writer and editor best known in comics for co-creating the character Isaiah Bradley in Marvel's "Truth: Red, White & Black."
  • C. David Morales
    David Morales is an influential American DJ and Grammy-winning house music producer known for his remixes and work with major pop and dance artists.
  • D. Daniel Morales
    Daniel Morales is the reckless yet highly skilled Marseille taxi driver and protagonist of the French action-comedy Taxi film series.
  • E. Juan Morales
    Juan Morales was a Mexican military commander known for leading forces during the Siege of Veracruz in the Mexican–American War.
  • 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_69d827894ac0819097803e57f3227b23 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de61df628c8190ba3f557e2128dce5 completed April 14, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe967cea3c81909d9b600501897a41 completed May 9, 2026, 2:05 a.m.
Created at: April 10, 2026, 1:04 a.m.