Triple

T1577932
Position Surface form Disambiguated ID Type / Status
Subject Bob Hoskins E33695 entity
Predicate name P16 FINISHED
Object Bob Hoskins E33695 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: Bob Hoskins | Statement: [Bob Hoskins, name, Bob Hoskins]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bob Hoskins
Context triple: [Bob Hoskins, name, Bob Hoskins]
  • A. Bob Hoskins chosen
    Bob Hoskins was an acclaimed English actor known for his intense, often gritty performances in films such as "The Long Good Friday," "Mona Lisa," and "Who Framed Roger Rabbit."
  • B. Danny Glover
    Danny Glover is an American actor and activist best known for his roles in films such as the "Lethal Weapon" series and "The Color Purple."
  • C. Eric Roberts
    Eric Roberts is an American actor known for his prolific film and television career, including an iconic turn as the villainous Time Lord known as the Master in the 1996 Doctor Who TV movie.
  • D. Tommy Lee Jones
    Tommy Lee Jones is an American actor and filmmaker known for his tough, stoic characters in films such as "The Fugitive," "No Country for Old Men," and "Men in Black."
  • E. James Woods
    James Woods is an American actor known for his intense performances in film and television, including acclaimed roles in movies such as "Salvador," "Videodrome," and "Casino."
  • 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_69a885f27a4c8190a4622252cdf54c00 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a908d571f081908acec43ff2ef112d completed March 5, 2026, 4:38 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad719f91cc8190aaacaa583098732a completed March 8, 2026, 12:54 p.m.
Created at: March 4, 2026, 7:27 p.m.