Triple
T7549290
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fagan |
E178487
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Sean Fagan
Sean Fagan is a notable individual whose prominence has led to recognition of the surname Fagan through his achievements.
|
E691850
|
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: Sean Fagan | Statement: [Fagan, hasNotableBearer, Sean Fagan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sean Fagan Context triple: [Fagan, hasNotableBearer, Sean Fagan]
-
A.
Dan Fagan
Dan Fagan is a notable individual recognized for achievements associated with the surname Fagan.
-
B.
Sean Kilpatrick
Sean Kilpatrick is an American professional basketball player known for his scoring ability as a guard in the NBA and overseas leagues.
-
C.
Matt Fenton
Matt Fenton is a British theatre director and arts leader known for his innovative, youth-focused programming and leadership within the UK performing arts sector.
-
D.
Brian Flanagan
Brian Flanagan is a fictional bartender and main character from the 1988 film "Cocktail," portrayed by Tom Cruise.
-
E.
Brian Fitzpatrick
Brian Fitzpatrick is an American Republican politician and former FBI agent who has served as a U.S. Representative from Pennsylvania.
- 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: Sean Fagan Triple: [Fagan, hasNotableBearer, Sean Fagan]
Generated description
Sean Fagan is a notable individual whose prominence has led to recognition of the surname Fagan through his achievements.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sean Fagan Target entity description: Sean Fagan is a notable individual whose prominence has led to recognition of the surname Fagan through his achievements.
-
A.
Dan Fagan
Dan Fagan is a notable individual recognized for achievements associated with the surname Fagan.
-
B.
Sean Kilpatrick
Sean Kilpatrick is an American professional basketball player known for his scoring ability as a guard in the NBA and overseas leagues.
-
C.
Matt Fenton
Matt Fenton is a British theatre director and arts leader known for his innovative, youth-focused programming and leadership within the UK performing arts sector.
-
D.
Brian Flanagan
Brian Flanagan is a fictional bartender and main character from the 1988 film "Cocktail," portrayed by Tom Cruise.
-
E.
Brian Fitzpatrick
Brian Fitzpatrick is an American Republican politician and former FBI agent who has served as a U.S. Representative from Pennsylvania.
- 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_69c69f2cbe08819088f9eb0c03ef529b |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f8b35ba481908e1e5bbf329daa33 |
completed | March 27, 2026, 9:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c9bcbe7f488190aee034a51e8a281b |
completed | March 29, 2026, 11:58 p.m. |
| NEDg | Description generation | batch_69c9bd2305a481909ac1ce38edf50650 |
completed | March 30, 2026, midnight |
| NED2 | Entity disambiguation (via description) | batch_69c9bdbf97188190a0a97d8a832f54f4 |
completed | March 30, 2026, 12:03 a.m. |
Created at: March 27, 2026, 3:49 p.m.