Triple

T4331282
Position Surface form Disambiguated ID Type / Status
Subject Conan the Destroyer E96753 entity
Predicate cinematographyBy P1953 FINISHED
Object Jack Cardiff E226347 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: Jack Cardiff | Statement: [Conan the Destroyer, cinematographyBy, Jack Cardiff]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jack Cardiff
Context triple: [Conan the Destroyer, cinematographyBy, Jack Cardiff]
  • A. Jack Cardiff chosen
    Jack Cardiff was an acclaimed British cinematographer and director renowned for his pioneering use of Technicolor and visually striking work on classic films.
  • B. Jack Hawkins
    Jack Hawkins was a distinguished British actor known for his commanding presence in mid-20th-century war and historical films.
  • C. Michael Wilding
    Michael Wilding was a British film and stage actor best known for his roles in 1940s–1950s British cinema and for his high-profile marriage to actress Elizabeth Taylor.
  • D. George Brent
    George Brent was an Irish-American leading man of 1930s and 1940s Hollywood cinema, known for his suave screen presence opposite stars like Bette Davis.
  • E. Trevor Howard
    Trevor Howard was a distinguished English film and stage actor best known for his roles in classic films such as "Brief Encounter" and "The Third Man."
  • 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_69b34542fd908190b11b08faad8decfd completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3514c39748190900e13e70ed8848c completed March 12, 2026, 11:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5db98ae888190aac5b5b7839ae7dd completed March 14, 2026, 10:05 p.m.
Created at: March 12, 2026, 11:13 p.m.