Triple

T9656966
Position Surface form Disambiguated ID Type / Status
Subject Hawkins E233482 entity
Predicate hasNotableBearer P458 FINISHED
Object Jack Hawkins E145577 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 Hawkins | Statement: [Hawkins, hasNotableBearer, Jack Hawkins]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jack Hawkins
Context triple: [Hawkins, hasNotableBearer, Jack Hawkins]
  • A. Jack Hawkins chosen
    Jack Hawkins was a distinguished British actor known for his commanding presence in mid-20th-century war and historical films.
  • B. 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."
  • 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 Powell
    George Powell was a 19th-century British sealer and explorer noted for his Antarctic voyages and co-discovery of several sub-Antarctic islands.
  • E. Jack Cardiff
    Jack Cardiff was an acclaimed British cinematographer and director renowned for his pioneering use of Technicolor and visually striking work on classic films.
  • 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_69ca848c1ba88190b84b410cd14627fc completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9bdd5c0c8190a6c82a1609454d1b completed April 1, 2026, 10:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69d19f6d397481908f7db1f272a6a710 completed April 4, 2026, 11:31 p.m.
Created at: March 30, 2026, 8:14 p.m.