Triple

T13439047
Position Surface form Disambiguated ID Type / Status
Subject Sweeney E320304 entity
Predicate hasNotableBearer P458 FINISHED
Object Con Sweeney
Con Sweeney is a notable individual bearing the surname Sweeney, recognized enough to be specifically distinguished among people with that name.
E1045021 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: Con Sweeney | Statement: [Sweeney, hasNotableBearer, Con Sweeney]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Con Sweeney
Context triple: [Sweeney, hasNotableBearer, Con Sweeney]
  • A. Sam Sweeney
    Sam Sweeney is a recurring character on the TV sitcom "New Girl," known as one of Jessica Day’s significant romantic partners.
  • B. Joe Sweeney
    Joe Sweeney is a relatively common personal name shared by multiple individuals across fields such as politics, sports, and the arts.
  • C. Day O’Connor
    Day O’Connor is the family name of Sandra Day O’Connor, the first woman to serve as a Justice on the United States Supreme Court.
  • D. Jack O'Conner
    Jack O'Conner is a minor character in the Fast & Furious film franchise, known as the young son of protagonist Brian O'Conner and Mia Toretto.
  • E. Tom Henighan
    Tom Henighan is a researcher and co-author known for his work in large-scale language models and AI, including contributions to influential OpenAI publications.
  • 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: Con Sweeney
Triple: [Sweeney, hasNotableBearer, Con Sweeney]
Generated description
Con Sweeney is a notable individual bearing the surname Sweeney, recognized enough to be specifically distinguished among people with that name.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Con Sweeney
Target entity description: Con Sweeney is a notable individual bearing the surname Sweeney, recognized enough to be specifically distinguished among people with that name.
  • A. Sam Sweeney
    Sam Sweeney is a recurring character on the TV sitcom "New Girl," known as one of Jessica Day’s significant romantic partners.
  • B. Joe Sweeney
    Joe Sweeney is a relatively common personal name shared by multiple individuals across fields such as politics, sports, and the arts.
  • C. Day O’Connor
    Day O’Connor is the family name of Sandra Day O’Connor, the first woman to serve as a Justice on the United States Supreme Court.
  • D. Jack O'Conner
    Jack O'Conner is a minor character in the Fast & Furious film franchise, known as the young son of protagonist Brian O'Conner and Mia Toretto.
  • E. Tom Henighan
    Tom Henighan is a researcher and co-author known for his work in large-scale language models and AI, including contributions to influential OpenAI publications.
  • 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_69d80761e6cc8190a90c844589998ecc completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbaee5ec488190bd0c1e990dbd2bc2 completed April 12, 2026, 2:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7547880d48190af9b30e4e521a952 completed May 3, 2026, 1:58 p.m.
NEDg Description generation batch_69f75585cac88190bcf3fcd714d73b1b completed May 3, 2026, 2:02 p.m.
NED2 Entity disambiguation (via description) batch_69f7561f170c8190b12c79fbbe57ad91 completed May 3, 2026, 2:05 p.m.
Created at: April 9, 2026, 9:40 p.m.