Triple

T1220097
Position Surface form Disambiguated ID Type / Status
Subject Gage E26199 entity
Predicate hasNotableBearer P458 FINISHED
Object Kevin Gage
Kevin Gage is an American actor best known for his intense supporting roles in films such as "Heat" and "G.I. Jane."
E263621 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: Kevin Gage | Statement: [Gage, hasNotableBearer, Kevin Gage]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kevin Gage
Context triple: [Gage, hasNotableBearer, Kevin Gage]
  • A. Kevin Yagher
    Kevin Yagher is an American special effects and makeup artist and director best known for his work on horror and fantasy films and for creating iconic genre characters.
  • B. Kevin Hageman
    Kevin Hageman is an American screenwriter and producer known for his work on animated and family films and television series, including contributions to The Lego Movie franchise.
  • C. Joe Gayton
    Joe Gayton is an American screenwriter and producer best known for co-creating the Western television drama series "Hell on Wheels."
  • D. Greg Finton
    Greg Finton is a film editor known for his work on documentaries and feature films, including the acclaimed documentary "He Named Me Malala."
  • E. Greg Beeman
    Greg Beeman is an American television director and producer known for his work on genre series such as "Falling Skies," "Heroes," and "Smallville."
  • 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: Kevin Gage
Triple: [Gage, hasNotableBearer, Kevin Gage]
Generated description
Kevin Gage is an American actor best known for his intense supporting roles in films such as "Heat" and "G.I. Jane."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kevin Gage
Target entity description: Kevin Gage is an American actor best known for his intense supporting roles in films such as "Heat" and "G.I. Jane."
  • A. Kevin Yagher
    Kevin Yagher is an American special effects and makeup artist and director best known for his work on horror and fantasy films and for creating iconic genre characters.
  • B. Kevin Hageman
    Kevin Hageman is an American screenwriter and producer known for his work on animated and family films and television series, including contributions to The Lego Movie franchise.
  • C. Joe Gayton
    Joe Gayton is an American screenwriter and producer best known for co-creating the Western television drama series "Hell on Wheels."
  • D. Greg Finton
    Greg Finton is a film editor known for his work on documentaries and feature films, including the acclaimed documentary "He Named Me Malala."
  • E. Greg Beeman
    Greg Beeman is an American television director and producer known for his work on genre series such as "Falling Skies," "Heroes," and "Smallville."
  • 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_69a49484688c8190a1bf285eb396a8b6 completed March 1, 2026, 7:33 p.m.
NER Named-entity recognition batch_69a4be1ead088190bf44dc6ab1edf18b completed March 1, 2026, 10:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69aeb39a387c8190b5c1f4876532e376 completed March 9, 2026, 11:48 a.m.
NEDg Description generation batch_69aeb540ae008190aa5cbfa1c81540cc completed March 9, 2026, 11:55 a.m.
NED2 Entity disambiguation (via description) batch_69aeb59d0e5c819080bf5b34946b68ac completed March 9, 2026, 11:57 a.m.
Created at: March 1, 2026, 7:46 p.m.