Triple

T3478446
Position Surface form Disambiguated ID Type / Status
Subject Groves E73431 entity
Predicate hasNotableBearer P458 FINISHED
Object Paul Groves
Paul Groves is an American operatic tenor acclaimed for his performances in major international opera houses and concert halls.
E391535 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 Groves | Statement: [Groves, hasNotableBearer, Paul Groves]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paul Groves
Context triple: [Groves, hasNotableBearer, Paul Groves]
  • A. Christopher Greenbury
    Christopher Greenbury was a British film editor best known for his Academy Award–winning work on the 1999 drama "American Beauty."
  • B. Graham Rogers
    Graham Rogers is an American actor known for his roles in television series such as "The Kominsky Method," "Quantico," and "Atypical."
  • C. Graham Sharp
    Graham Sharp is an American banjo player, singer, and songwriter best known as a founding member of the bluegrass band Steep Canyon Rangers.
  • D. Graham Crowley
    Graham Crowley is a British painter known for his figurative and landscape works and for his influential role in contemporary British art since the late 20th century.
  • E. Phil Woolpert
    Phil Woolpert was a prominent American college basketball coach best known for leading the University of San Francisco to multiple national championships in the 1950s.
  • 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 Groves
Triple: [Groves, hasNotableBearer, Paul Groves]
Generated description
Paul Groves is an American operatic tenor acclaimed for his performances in major international opera houses and concert halls.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Paul Groves
Target entity description: Paul Groves is an American operatic tenor acclaimed for his performances in major international opera houses and concert halls.
  • A. Christopher Greenbury
    Christopher Greenbury was a British film editor best known for his Academy Award–winning work on the 1999 drama "American Beauty."
  • B. Graham Rogers
    Graham Rogers is an American actor known for his roles in television series such as "The Kominsky Method," "Quantico," and "Atypical."
  • C. Graham Sharp
    Graham Sharp is an American banjo player, singer, and songwriter best known as a founding member of the bluegrass band Steep Canyon Rangers.
  • D. Graham Crowley
    Graham Crowley is a British painter known for his figurative and landscape works and for his influential role in contemporary British art since the late 20th century.
  • E. Phil Woolpert
    Phil Woolpert was a prominent American college basketball coach best known for leading the University of San Francisco to multiple national championships in the 1950s.
  • 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_69ad85b3c9b08190857cae74c7f36da9 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adbb5ca73c81908256e3339a3a6f9f completed March 8, 2026, 6:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4faec5fc4819090c8f55b819d436c completed March 14, 2026, 6:06 a.m.
NEDg Description generation batch_69b4fc7abfb481908f563e17e6e57a4e completed March 14, 2026, 6:13 a.m.
NED2 Entity disambiguation (via description) batch_69b4fce0a6a88190be19941a70caebdc completed March 14, 2026, 6:14 a.m.
Created at: March 8, 2026, 3:17 p.m.