Triple

T18711738
Position Surface form Disambiguated ID Type / Status
Subject A Woman of Affairs E457529 entity
Predicate starring P1507 FINISHED
Object Johnny Mack Brown 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: Johnny Mack Brown | Statement: [A Woman of Affairs, starring, Johnny Mack Brown]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Johnny Mack Brown
Context triple: [A Woman of Affairs, starring, Johnny Mack Brown]
  • A. Johnny Mack Brown chosen
    Johnny Mack Brown was an American film actor and former college football star best known for his roles in Westerns during the 1930s and 1940s.
  • B. Buck Jones
    Buck Jones was a popular American Western film star of the 1920s and 1930s, known for his rugged cowboy roles and numerous B-movie adventures.
  • C. Tim Holt
    Tim Holt was an American film actor best known for his roles in Westerns and classic Hollywood films of the 1930s and 1940s.
  • D. Hoot Gibson
    Hoot Gibson was a popular American rodeo champion turned film actor and director, best known as one of the early cowboy stars of silent and early sound Western movies.
  • E. Raymond Griffith
    Raymond Griffith was a prominent American silent film comedian and producer known for his sophisticated, understated style and influential work in early Hollywood cinema.
  • 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_69d8d392aad081909fe31aa03e6e97d1 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5671c53988190bfc132c853cebd02 completed April 19, 2026, 11:37 p.m.
Created at: April 10, 2026, 11:50 a.m.