Triple

T3859823
Position Surface form Disambiguated ID Type / Status
Subject The Dogs of War E90107 entity
Predicate director P255 FINISHED
Object John Irvin
John Irvin is a British film director known for his work on war and action dramas, including the 1980 mercenary film "The Dogs of War."
E392254 NE FINISHED

How this triple was built (4 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: John Irvin | Statement: [The Dogs of War, director, John Irvin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John Irvin
Context triple: [The Dogs of War, director, John Irvin]
  • A. Russell Carpenter
    Russell Carpenter is an Academy Award–winning American cinematographer best known for his work on major films such as Titanic and other high-profile Hollywood productions.
  • B. Richard Maibaum
    Richard Maibaum was an American screenwriter and producer best known for his long-running work on the James Bond film series.
  • C. John Irwin
    John Irwin is a television producer best known for his work as an executive producer on major late-night talk shows, including The Jay Leno Show.
  • D. Richard Langer
    Richard Langer is a relatively obscure individual whose specific public notability is not clearly established from the available information.
  • E. Kevin Kiner
    Kevin Kiner is an American composer best known for his prolific work on film and television scores, including major franchises like Star Wars and DC Comics adaptations.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: John Irvin
Triple: [The Dogs of War, director, John Irvin]
Generated description
John Irvin is a British film director known for his work on war and action dramas, including the 1980 mercenary film "The Dogs of War."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: John Irvin
Target entity description: John Irvin is a British film director known for his work on war and action dramas, including the 1980 mercenary film "The Dogs of War."
  • A. Russell Carpenter
    Russell Carpenter is an Academy Award–winning American cinematographer best known for his work on major films such as Titanic and other high-profile Hollywood productions.
  • B. Richard Maibaum
    Richard Maibaum was an American screenwriter and producer best known for his long-running work on the James Bond film series.
  • C. John Irwin
    John Irwin is a television producer best known for his work as an executive producer on major late-night talk shows, including The Jay Leno Show.
  • D. Richard Langer
    Richard Langer is a relatively obscure individual whose specific public notability is not clearly established from the available information.
  • E. Kevin Kiner
    Kevin Kiner is an American composer best known for his prolific work on film and television scores, including major franchises like Star Wars and DC Comics adaptations.
  • F. None of above. chosen

Provenance (5 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_69aed95b3c088190a8f85d19e6070599 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeec1ff39c8190b83a88abd840a0e3 completed March 9, 2026, 3:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69b50424b23c8190b888cfb79e26e758 completed March 14, 2026, 6:45 a.m.
NEDg Description generation batch_69b504ff7624819089f98794ec97ed8f completed March 14, 2026, 6:49 a.m.
NED2 Entity disambiguation (via description) batch_69b50594e4888190b2db45eee2a988a7 completed March 14, 2026, 6:52 a.m.
Created at: March 9, 2026, 3:19 p.m.