Triple

T20657965
Position Surface form Disambiguated ID Type / Status
Subject Taxi 2 E507676 entity
Predicate mainCharacter P1183 FINISHED
Object Daniel Morales 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: Daniel Morales | Statement: [Taxi 2, mainCharacter, Daniel Morales]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Daniel Morales
Context triple: [Taxi 2, mainCharacter, Daniel Morales]
  • A. Daniel Morales chosen
    Daniel Morales is the reckless yet highly skilled Marseille taxi driver and protagonist of the French action-comedy Taxi film series.
  • B. 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.
  • C. Ricardo Morales
    Ricardo Morales is a grieving husband whose obsessive quest for justice drives much of the emotional and moral tension in the Argentine crime drama film "The Secret in Their Eyes."
  • D. Juan Morales
    Juan Morales was a Mexican military commander known for leading forces during the Siege of Veracruz in the Mexican–American War.
  • E. Roberto Morales
    Roberto Morales is a film and television producer known for his work on the project "Vivir."
  • 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_69e0b4bf58c081908e52a4500e03ff83 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6b2eefd5c8190a71d4be690a6ae0e completed April 20, 2026, 11:12 p.m.
Created at: April 16, 2026, 11:43 a.m.