Triple

T5043383
Position Surface form Disambiguated ID Type / Status
Subject Arrow in the Dust E113599 entity
Predicate director P255 FINISHED
Object Lesley Selander E523877 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: Lesley Selander | Statement: [Arrow in the Dust, director, Lesley Selander]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lesley Selander
Context triple: [Arrow in the Dust, director, Lesley Selander]
  • A. Lesley Selander chosen
    Lesley Selander was a prolific American film director best known for his work on mid-20th-century Westerns and action pictures.
  • B. Barbara Enberg
    Barbara Enberg is known as the wife of the late American sportscaster Dick Enberg.
  • C. Maureen Swanson
    Maureen Swanson was a British actress active in the 1950s, known for her roles in comedy and drama films before later becoming the Countess of Dudley.
  • D. Barbara Blomberg
    Barbara Blomberg was a 16th-century German woman best known as the mistress of Holy Roman Emperor Charles V and the mother of his illegitimate son, John of Austria (the Elder).
  • E. Carlene Olson
    Carlene Olson is an American actress and former model best known for her marriage to actor Michael Biehn.
  • 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_69bd44391fc48190a311ce9c826c209b completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd73fc04f08190aba851fa0192d0fb completed March 20, 2026, 4:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf70c59678819097aed5af25f36b66 completed March 22, 2026, 4:32 a.m.
Created at: March 20, 2026, 1:37 p.m.