Triple

T15019890
Position Surface form Disambiguated ID Type / Status
Subject Last Exit to Brooklyn E378055 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: [Last Exit to Brooklyn, castMember, Esai Morales]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Esai Morales
Context triple: [Last Exit to Brooklyn, 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. Carlos Mencia
    Carlos Mencia is a Honduran-American comedian and actor best known for his stand-up work and his Comedy Central show "Mind of Mencia."
  • D. 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.
  • E. Daniel Morales
    Daniel Morales is the reckless yet highly skilled Marseille taxi driver and protagonist of the French action-comedy Taxi film series.
  • 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_69d85cd3a3c881908c71fc424d459c17 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded76445988190984b57de66e00c4a completed April 15, 2026, 12:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff82dfbc28819090cf56f16b5e7c39 completed May 9, 2026, 6:54 p.m.
Created at: April 10, 2026, 2:56 a.m.