Triple
T12243967
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fastenal |
E291803
|
entity |
| Predicate | foundedBy |
P104
|
FINISHED |
| Object |
Bob Kierlin
Bob Kierlin is an American businessman best known as the founder of Fastenal, a major industrial and construction supplies distributor.
|
E972411
|
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: Bob Kierlin | Statement: [Fastenal, foundedBy, Bob Kierlin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bob Kierlin Context triple: [Fastenal, foundedBy, Bob Kierlin]
-
A.
Trent Olsen
Trent Olsen is an American former child actor and the older brother of actresses Mary-Kate, Ashley, and Elizabeth Olsen.
-
B.
Travis Goff
Travis Goff is a college athletics administrator who serves as the athletic director at the University of Kansas, overseeing the Jayhawks’ sports programs.
-
C.
Matt Flynn
Matt Flynn is an American drummer best known as a longtime member of the pop-rock band Maroon 5.
-
D.
Troy Bowles
Troy Bowles is the son of NFL head coach Todd Bowles and a high school football linebacker who has been a notable college recruit.
-
E.
Chad Feldheimer
Chad Feldheimer is a dim-witted but enthusiastic gym employee whose discovery of what he believes to be sensitive government information drives much of the darkly comic chaos in the film "Burn After Reading."
- 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: Bob Kierlin Triple: [Fastenal, foundedBy, Bob Kierlin]
Generated description
Bob Kierlin is an American businessman best known as the founder of Fastenal, a major industrial and construction supplies distributor.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bob Kierlin Target entity description: Bob Kierlin is an American businessman best known as the founder of Fastenal, a major industrial and construction supplies distributor.
-
A.
Trent Olsen
Trent Olsen is an American former child actor and the older brother of actresses Mary-Kate, Ashley, and Elizabeth Olsen.
-
B.
Travis Goff
Travis Goff is a college athletics administrator who serves as the athletic director at the University of Kansas, overseeing the Jayhawks’ sports programs.
-
C.
Matt Flynn
Matt Flynn is an American drummer best known as a longtime member of the pop-rock band Maroon 5.
-
D.
Troy Bowles
Troy Bowles is the son of NFL head coach Todd Bowles and a high school football linebacker who has been a notable college recruit.
-
E.
Chad Feldheimer
Chad Feldheimer is a dim-witted but enthusiastic gym employee whose discovery of what he believes to be sensitive government information drives much of the darkly comic chaos in the film "Burn After Reading."
- 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_69d6ab67950c8190be08450a06228c4b |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91cb724448190be29fc1d2b946ab7 |
completed | April 10, 2026, 3:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f60ab7b9308190b621b71d75aa10cc |
completed | May 2, 2026, 2:31 p.m. |
| NEDg | Description generation | batch_69f60c6211448190af411f1b6f42c4b6 |
completed | May 2, 2026, 2:38 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f60d1429f08190b7f3f053044f5a9e |
completed | May 2, 2026, 2:41 p.m. |
Created at: April 8, 2026, 9:51 p.m.