Triple

T13220024
Position Surface form Disambiguated ID Type / Status
Subject So Many Pros E314724 entity
Predicate performer P1363 FINISHED
Object Charlie Wilson E337892 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: Charlie Wilson | Statement: [So Many Pros, performer, Charlie Wilson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Charlie Wilson
Context triple: [So Many Pros, performer, Charlie Wilson]
  • A. Charlie Wilson
    Charlie Wilson was a U.S. Congressman from Texas known for orchestrating covert support to Afghan mujahideen during the Soviet–Afghan War, an effort dramatized in the film "Charlie Wilson's War."
  • B. Charlie Wilson chosen
    Charlie Wilson is an American R&B and soul singer best known as the former lead vocalist of The Gap Band and for his successful solo career.
  • C. Robert Hays
    Robert Hays is an American actor best known for his comedic lead role as the nervous pilot Ted Striker in the classic parody film "Airplane!" and its sequel.
  • D. Richard Johnson
    Richard Johnson is the husband of Francesca Johnson, a character in the romantic drama "The Bridges of Madison County."
  • E. Richard Johnson
    Richard Johnson was a British actor known for his work in mid-20th-century film and television, including prominent roles in war and horror movies.
  • 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_69d806affc688190a25b6ccc588e9c72 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98cf581508190883033f0c961736a completed April 10, 2026, 11:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f716c4a71c8190b0e0ae40af115c64 completed May 3, 2026, 9:35 a.m.
Created at: April 9, 2026, 9:18 p.m.