Triple

T14765295
Position Surface form Disambiguated ID Type / Status
Subject Irvin Irving E346976 entity
Predicate associatedWith P37 FINISHED
Object Harry Bosch E379930 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: Harry Bosch | Statement: [Irvin Irving, associatedWith, Harry Bosch]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Harry Bosch
Context triple: [Irvin Irving, associatedWith, Harry Bosch]
  • A. Harry Bosch chosen
    Harry Bosch is a hard-boiled Los Angeles homicide detective and the central protagonist of Michael Connelly’s long-running crime novel series.
  • B. Harry Block
    Harry Block is the neurotic, self-absorbed writer protagonist of Woody Allen’s film "Deconstructing Harry," whose chaotic personal life fuels his fiction.
  • C. Ed McBain
    Ed McBain was the pen name of American author Evan Hunter, best known for his influential 87th Precinct police procedural novels and his significant impact on modern crime fiction.
  • D. Inspector Harry Callahan
    Inspector Harry Callahan is a tough, no-nonsense San Francisco police detective famously portrayed by Clint Eastwood in the Dirty Harry film series.
  • E. Frank Roarke
    Frank Roarke is a veteran, morally ambiguous LAPD detective who mentors a rookie cop in the television adaptation of "Training Day."
  • 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_69d822e8896c819091169882f9b20486 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dec7f576c881909da70627f5897c94 completed April 14, 2026, 11:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe388aeb9c819099a987a819959479 completed May 8, 2026, 7:24 p.m.
Created at: April 10, 2026, 1:30 a.m.