Triple

T2692921
Position Surface form Disambiguated ID Type / Status
Subject Durkan E58445 entity
Predicate hasNotableBearer P458 FINISHED
Object Patrick Durkan
Patrick Durkan is a notable individual who shares the Durkan surname and has achieved sufficient recognition to be specifically cited as a bearer of the name.
 E300343 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: Patrick Durkan | Statement: [Durkan, hasNotableBearer, Patrick Durkan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Patrick Durkan
Context triple: [Durkan, hasNotableBearer, Patrick Durkan]
  • A. Tom Durkan
    Tom Durkan is a notable individual recognized for his association with the Durkan name, likely distinguished in a professional or public capacity.
  • B. John Durkan
    John Durkan is a notable individual distinguished enough in his field or public life to be specifically recognized as a bearer of the surname Durkan.
  • C. Michael Durkan
    Michael Durkan is a notable individual who shares the Durkan surname, recognized as a distinguished bearer of that family name.
  • D. Andrew Duggan
    Andrew Duggan was an American character actor known for his prolific work in film and television from the 1950s through the 1980s.
  • E. Sean Maguire
    Sean Maguire is the compassionate, tough-minded therapist and widowed professor who mentors Will Hunting in the film "Good Will Hunting."
  • 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: Patrick Durkan
Triple: [Durkan, hasNotableBearer, Patrick Durkan]
Generated description
Patrick Durkan is a notable individual who shares the Durkan surname and has achieved sufficient recognition to be specifically cited as a bearer of the name.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Patrick Durkan
Target entity description: Patrick Durkan is a notable individual who shares the Durkan surname and has achieved sufficient recognition to be specifically cited as a bearer of the name.
  • A. Tom Durkan
    Tom Durkan is a notable individual recognized for his association with the Durkan name, likely distinguished in a professional or public capacity.
  • B. John Durkan
    John Durkan is a notable individual distinguished enough in his field or public life to be specifically recognized as a bearer of the surname Durkan.
  • C. Michael Durkan
    Michael Durkan is a notable individual who shares the Durkan surname, recognized as a distinguished bearer of that family name.
  • D. Andrew Duggan
    Andrew Duggan was an American character actor known for his prolific work in film and television from the 1950s through the 1980s.
  • E. Sean Maguire
    Sean Maguire is the compassionate, tough-minded therapist and widowed professor who mentors Will Hunting in the film "Good Will Hunting."
  • 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_69ab4ac269e481909cb317d79e68b75b completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abda0dd97c81909a60cf200f57c087 completed March 7, 2026, 7:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69afc63b76e0819084c4d2bd4a9e6d78 completed March 10, 2026, 7:20 a.m.
NEDg Description generation batch_69afcaaca2148190b61498e5139d664d completed March 10, 2026, 7:39 a.m.
NED2 Entity disambiguation (via description) batch_69afcb43e9b88190a99b1bb2e62430da completed March 10, 2026, 7:41 a.m.
Created at: March 6, 2026, 9:54 p.m.