Triple

T18375748
Position Surface form Disambiguated ID Type / Status
Subject Meaney E446307 entity
Predicate hasNotableBearer P458 FINISHED
Object John Meaney
John Meaney is a British science fiction author known for his technologically rich, philosophically infused novels that blend hard science with noir and cyberpunk elements.
E1324651 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 Meaney | Statement: [Meaney, hasNotableBearer, John Meaney]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John Meaney
Context triple: [Meaney, hasNotableBearer, John Meaney]
  • A. Thomas Keenan
    Thomas Keenan is a name shared by several notable individuals, including scholars, writers, and public figures across various fields.
  • B. Tim O'Connor
    Tim O'Connor is a New Zealand educational leader best known for serving as rector of the prestigious Auckland Grammar School.
  • C. Joe Sweeney
    Joe Sweeney is a relatively common personal name shared by multiple individuals across fields such as politics, sports, and the arts.
  • D. Kevin Rooney
    Kevin Rooney is an American boxing trainer best known for coaching Mike Tyson during his rise to the heavyweight championship in the 1980s.
  • E. Brian Sweeney
    Brian Sweeney is a relatively common personal name shared by multiple individuals, including professionals in fields such as sports, business, and the arts.
  • 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 Meaney
Triple: [Meaney, hasNotableBearer, John Meaney]
Generated description
John Meaney is a British science fiction author known for his technologically rich, philosophically infused novels that blend hard science with noir and cyberpunk elements.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: John Meaney
Target entity description: John Meaney is a British science fiction author known for his technologically rich, philosophically infused novels that blend hard science with noir and cyberpunk elements.
  • A. Thomas Keenan
    Thomas Keenan is a name shared by several notable individuals, including scholars, writers, and public figures across various fields.
  • B. Tim O'Connor
    Tim O'Connor is a New Zealand educational leader best known for serving as rector of the prestigious Auckland Grammar School.
  • C. Joe Sweeney
    Joe Sweeney is a relatively common personal name shared by multiple individuals across fields such as politics, sports, and the arts.
  • D. Kevin Rooney
    Kevin Rooney is an American boxing trainer best known for coaching Mike Tyson during his rise to the heavyweight championship in the 1980s.
  • E. Brian Sweeney
    Brian Sweeney is a relatively common personal name shared by multiple individuals, including professionals in fields such as sports, business, and the arts.
  • 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_69d8b9f370b88190b1e5081c2c238e7f completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e51759353481908aa2de599fd2cf3b completed April 19, 2026, 5:56 p.m.
NED1 Entity disambiguation (via context triple) batch_6a040fd060ac819085c23e931203ec3d completed May 13, 2026, 5:44 a.m.
NEDg Description generation batch_6a0410995964819093a16a750fd81319 completed May 13, 2026, 5:48 a.m.
NED2 Entity disambiguation (via description) batch_6a04110bce308190b2c6f0c78708b84d completed May 13, 2026, 5:50 a.m.
Created at: April 10, 2026, 10:45 a.m.