Triple

T13866996
Position Surface form Disambiguated ID Type / Status
Subject Welsh Open E333349 entity
Predicate hasNotableChampion P2766 FINISHED
Object Paul Hunter
Paul Hunter was an English professional snooker player renowned for his flair, charisma, and multiple major ranking titles before his career was cut short by his early death.
 E1066645 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: Paul Hunter | Statement: [Welsh Open, hasNotableChampion, Paul Hunter]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Paul Hunter
Context triple: [Welsh Open, hasNotableChampion, Paul Hunter]
  • A. Paul Hunter
    Paul Hunter is an acclaimed American music video director known for his visually innovative work with major artists across hip-hop, R&B, and pop.
  • B. Paul Hunter
    Paul Hunter is a film editor known for his work on animated feature films such as "The Nut Job."
  • C. John Higgins
    John Higgins is a British comic book artist and colorist best known for his influential work on landmark graphic novels such as Watchmen.
  • D. John Higgins
    John Higgins is a Scottish professional snooker player widely regarded as one of the sport’s all-time greats, known for multiple world titles and exceptional tactical play.
  • E. Paul Groth
    Paul Groth is a computer scientist known for his work in knowledge representation, semantic web technologies, and data provenance.
  • 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: Paul Hunter
Triple: [Welsh Open, hasNotableChampion, Paul Hunter]
Generated description
Paul Hunter was an English professional snooker player renowned for his flair, charisma, and multiple major ranking titles before his career was cut short by his early death.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Paul Hunter
Target entity description: Paul Hunter was an English professional snooker player renowned for his flair, charisma, and multiple major ranking titles before his career was cut short by his early death.
  • A. Paul Hunter
    Paul Hunter is an acclaimed American music video director known for his visually innovative work with major artists across hip-hop, R&B, and pop.
  • B. Paul Hunter
    Paul Hunter is a film editor known for his work on animated feature films such as "The Nut Job."
  • C. John Higgins
    John Higgins is a British comic book artist and colorist best known for his influential work on landmark graphic novels such as Watchmen.
  • D. John Higgins
    John Higgins is a Scottish professional snooker player widely regarded as one of the sport’s all-time greats, known for multiple world titles and exceptional tactical play.
  • E. Paul Groth
    Paul Groth is a computer scientist known for his work in knowledge representation, semantic web technologies, and data provenance.
  • 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_69d81c5ced9c8190b0e9bcc6effe5959 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de05c419d481909230e8879b6dab5c completed April 14, 2026, 9:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7c1039128819086cfe9f966b9f142 completed May 3, 2026, 9:41 p.m.
NEDg Description generation batch_69f7c1e7efd88190ac07472647da69e7 completed May 3, 2026, 9:45 p.m.
NED2 Entity disambiguation (via description) batch_69f7c33c2f34819084502d5f03f09ddd completed May 3, 2026, 9:50 p.m.
Created at: April 9, 2026, 10:14 p.m.