Triple

T10719625
Position Surface form Disambiguated ID Type / Status
Subject Marshal Will Kane E252782 entity
Predicate spouse P13 FINISHED
Object Amy Fowler Kane E257314 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: Amy Fowler Kane | Statement: [Marshal Will Kane, spouse, Amy Fowler Kane]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Amy Fowler Kane
Context triple: [Marshal Will Kane, spouse, Amy Fowler Kane]
  • A. Amy Fowler Kane chosen
    Amy Fowler Kane is the pacifist Quaker wife of Marshal Will Kane in the classic Western film "High Noon," whose moral conflict and ultimate decision play a pivotal role in the story's climax.
  • B. Mary Dixon
    Mary Dixon is a fictional character from the long-running British television police drama "Dixon of Dock Green."
  • C. Evelyn Carnahan
    Evelyn Carnahan is a brilliant and adventurous English Egyptologist and librarian who serves as a central heroine in the 1999 film "The Mummy" and its sequels.
  • D. Amy Prentiss
    Amy Prentiss is a 1970s American television crime drama series featuring Jessica Walter as a pioneering female chief of detectives in San Francisco.
  • E. Nancy Grey
    Nancy Grey is a fictional character from the film "Red Dog," contributing to the story’s emotional depth and relationships surrounding the legendary kelpie.
  • 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_69d6aa5d8be481909a43218b2bfdbe95 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6ff3722ec8190b2d78a5630bf6efc completed April 9, 2026, 1:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69dbd9df306881908aef5c6e8b4e78dc completed April 12, 2026, 5:43 p.m.
Created at: April 8, 2026, 9:13 p.m.