Triple

T7931823
Position Surface form Disambiguated ID Type / Status
Subject Hennessy E184205 entity
Predicate hasNotableBearer P458 FINISHED
Object Thomas Hennessy
Thomas Hennessy is a notable individual distinguished enough to be recognized as a prominent bearer of the Hennessy surname.
 E724907 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: Thomas Hennessy | Statement: [Hennessy, hasNotableBearer, Thomas Hennessy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Thomas Hennessy
Context triple: [Hennessy, hasNotableBearer, Thomas Hennessy]
  • A. Paul Hennessy
    Paul Hennessy is the overprotective yet well-meaning father and newspaper columnist at the center of the sitcom "8 Simple Rules."
  • B. Patrick Hennessy
    Patrick Hennessy is a notable Irish painter recognized for his highly realistic and often introspective figurative and still-life works.
  • C. John Doherty
    John Doherty is known as the husband of American actress Michael Learned, famed for her role as Olivia Walton on the television series "The Waltons."
  • D. Bill Heelan
    Bill Heelan is a developer best known for creating the software project Archie.
  • E. Francis Keally
    Francis Keally was an American architect best known for his work on major public buildings in the early 20th century, particularly in New York City.
  • 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: Thomas Hennessy
Triple: [Hennessy, hasNotableBearer, Thomas Hennessy]
Generated description
Thomas Hennessy is a notable individual distinguished enough to be recognized as a prominent bearer of the Hennessy surname.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Thomas Hennessy
Target entity description: Thomas Hennessy is a notable individual distinguished enough to be recognized as a prominent bearer of the Hennessy surname.
  • A. Paul Hennessy
    Paul Hennessy is the overprotective yet well-meaning father and newspaper columnist at the center of the sitcom "8 Simple Rules."
  • B. Patrick Hennessy
    Patrick Hennessy is a notable Irish painter recognized for his highly realistic and often introspective figurative and still-life works.
  • C. John Doherty
    John Doherty is known as the husband of American actress Michael Learned, famed for her role as Olivia Walton on the television series "The Waltons."
  • D. Bill Heelan
    Bill Heelan is a developer best known for creating the software project Archie.
  • E. Francis Keally
    Francis Keally was an American architect best known for his work on major public buildings in the early 20th century, particularly in New York City.
  • 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_69ca8290c21c8190906a5ca6fe2b03c4 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3ace87f081908635769942645e78 completed March 31, 2026, 3:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd943f5aec8190a42d3932ef7c54fd completed April 1, 2026, 9:55 p.m.
NEDg Description generation batch_69cda62070888190b55b3f54d29e28e7 completed April 1, 2026, 11:11 p.m.
NED2 Entity disambiguation (via description) batch_69cdb21a65d88190a19dd41f95d173c8 completed April 2, 2026, 12:02 a.m.
Created at: March 30, 2026, 5:07 p.m.