Triple

T14119478
Position Surface form Disambiguated ID Type / Status
Subject Gene de Paul E339867 entity
Predicate name P16 FINISHED
Object Gene de Paul E339867 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: Gene de Paul | Statement: [Gene de Paul, name, Gene de Paul]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gene de Paul
Context triple: [Gene de Paul, name, Gene de Paul]
  • A. Gene de Paul chosen
    Gene de Paul was an American composer and songwriter known for his work on classic Hollywood films and popular songs in the mid-20th century.
  • B. Roger Blin
    Roger Blin was a French actor and theatre director best known for staging the original productions of Samuel Beckett’s plays, including the landmark premiere of "Waiting for Godot."
  • C. Don P. Francis
    Don P. Francis is an American epidemiologist and public health official known for his pioneering work on HIV/AIDS research and prevention at the Centers for Disease Control and Prevention.
  • D. Michel Drach
    Michel Drach was a French film director and screenwriter known for his intimate, socially engaged dramas in postwar French cinema.
  • E. Robert DeGuerin
    Robert DeGuerin is a corrupt and ruthless antagonist in the 1996 action film "Eraser," serving as a key villain opposing Arnold Schwarzenegger's character.
  • 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_69d81c6a95b481909e39111e0c1f31ee completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de609322ac8190bb389ca250882af5 completed April 14, 2026, 3:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcd0bc60088190a7e2f0c9532304e3 completed May 7, 2026, 5:49 p.m.
Created at: April 9, 2026, 10:22 p.m.