Triple

T8329444
Position Surface form Disambiguated ID Type / Status
Subject Every Which Way but Loose E195037 entity
Predicate setting P1957 FINISHED
Object California E26 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: California | Statement: [Every Which Way but Loose, setting, California]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: California
Context triple: [Every Which Way but Loose, setting, California]
  • A. Kalifornia
    Kalifornia is a 1993 neo-noir road thriller film that follows a journalist couple researching serial killers while unknowingly traveling with one.
  • B. California, United States chosen
    California, United States is a large and populous U.S. state on the West Coast known for its diverse geography, major technology and entertainment industries, and cultural and economic influence.
  • C. CA
    CA is the two-letter ISO 3166-1 alpha-2 country code that uniquely identifies Canada in international standards and systems.
  • D. CA
    CA is the commonly used abbreviation for Club Africain, a major Tunisian multi-sport club best known for its football team based in Tunis.
  • E. CA
    CA is the vehicle registration code used on license plates for the Italian city of Cagliari.
  • 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_69ca82e87f2c8190bdb71ee29dfc642d completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7fb812508190aed8a283dacf712e completed March 31, 2026, 8:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd958cf0808190af59e36c35b91e58 completed April 1, 2026, 10 p.m.
Created at: March 30, 2026, 5:56 p.m.