Triple

T8934387
Position Surface form Disambiguated ID Type / Status
Subject Morrow E212738 entity
Predicate hasNotableBearer P458 FINISHED
Object Phil Morrow
Phil Morrow is a television producer known for his work in developing and producing various entertainment and factual programs.
E783594 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: Phil Morrow | Statement: [Morrow, hasNotableBearer, Phil Morrow]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Phil Morrow
Context triple: [Morrow, hasNotableBearer, Phil Morrow]
  • A. Phil Burke
    Phil Burke is a Canadian actor best known for his role as Mickey McGinnes on the television drama series "Hell on Wheels."
  • B. Joe Dougherty
    Joe Dougherty was an American voice actor best known for originating the voice of the Warner Bros. cartoon character Porky Pig in the 1930s.
  • C. Greg Gilmore
    Greg Gilmore is an American rock drummer best known for his work with the late-1980s Seattle band Mother Love Bone, a key precursor to the grunge movement.
  • D. Michael Dorman
    Michael Dorman is an Australian actor known for his roles in television series such as "For All Mankind," "Patriot," and "The Secret Life of Us."
  • E. Stephen Holbrook
    Stephen Holbrook is a notable individual recognized for his contributions in his professional field, though specific widely known details about his work are not clearly established from the given information.
  • 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: Phil Morrow
Triple: [Morrow, hasNotableBearer, Phil Morrow]
Generated description
Phil Morrow is a television producer known for his work in developing and producing various entertainment and factual programs.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Phil Morrow
Target entity description: Phil Morrow is a television producer known for his work in developing and producing various entertainment and factual programs.
  • A. Phil Burke
    Phil Burke is a Canadian actor best known for his role as Mickey McGinnes on the television drama series "Hell on Wheels."
  • B. Joe Dougherty
    Joe Dougherty was an American voice actor best known for originating the voice of the Warner Bros. cartoon character Porky Pig in the 1930s.
  • C. Greg Gilmore
    Greg Gilmore is an American rock drummer best known for his work with the late-1980s Seattle band Mother Love Bone, a key precursor to the grunge movement.
  • D. Michael Dorman
    Michael Dorman is an Australian actor known for his roles in television series such as "For All Mankind," "Patriot," and "The Secret Life of Us."
  • E. Stephen Holbrook
    Stephen Holbrook is a notable individual recognized for his contributions in his professional field, though specific widely known details about his work are not clearly established from the given information.
  • 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_69ca8395c438819087d7cb844ab5990c completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc669138b48190a6bb4968f029a69e completed April 1, 2026, 12:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69d05be377988190a59f0033322d627f completed April 4, 2026, 12:31 a.m.
NEDg Description generation batch_69d05cb45280819096747ff8f7d5c2a0 completed April 4, 2026, 12:35 a.m.
NED2 Entity disambiguation (via description) batch_69d05d5d29f4819081c28b24cb2058b0 completed April 4, 2026, 12:37 a.m.
Created at: March 30, 2026, 6:58 p.m.