Triple

T18522942
Position Surface form Disambiguated ID Type / Status
Subject Sidney Lanfield E452634 entity
Predicate directed P7373 FINISHED
Object The Lady from Texas 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: The Lady from Texas | Statement: [Sidney Lanfield, directed, The Lady from Texas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: The Lady from Texas
Context triple: [Sidney Lanfield, directed, The Lady from Texas]
  • A. The Lady from Texas chosen
    The Lady from Texas is a 1951 American Western comedy film featuring Josephine Hull in a prominent role.
  • B. The Lady from Louisiana
    The Lady from Louisiana is a 1941 American crime drama film set in New Orleans, known for its blend of romance, political corruption, and natural disaster spectacle.
  • C. The Man from Texas
    The Man from Texas is a 1948 American Western film featuring actor James Craig in a leading role.
  • D. The Cowboy and the Lady
    The Cowboy and the Lady is a 1938 romantic comedy film starring Gary Cooper and Merle Oberon that earned recognition for its sound recording at the Academy Awards.
  • E. The Cowboy and the Lady
    The Cowboy and the Lady is a 1922 silent Western film featuring actress Priscilla Bonner in a prominent role.
  • 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_69d8d386df84819092355ebb260d848e completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5338f6da48190bdb374019d10db05 completed April 19, 2026, 7:57 p.m.
Created at: April 10, 2026, 11:37 a.m.