Triple
T6274160
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jenkins |
E140612
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Billy Jenkins
Billy Jenkins is a name shared by several notable individuals, including musicians and athletes, recognized within their respective fields.
|
E580409
|
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: Billy Jenkins | Statement: [Jenkins, hasNotableBearer, Billy Jenkins]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Billy Jenkins Context triple: [Jenkins, hasNotableBearer, Billy Jenkins]
-
A.
Michael Jenkins
Michael Jenkins is a theatre producer best known for his work on the hit musical comedy "Spamalot."
-
B.
Michael Jenkins
Michael Jenkins is an Australian screenwriter and director known for his work in film and television, including influential Australian dramas.
-
C.
Allen Jenkins
Allen Jenkins was an American character actor known for his comic supporting roles in numerous Hollywood films of the 1930s and 1940s.
-
D.
Jeff Jenkins
Jeff Jenkins is a television producer best known for his work on reality TV series, particularly within the Kardashian franchise.
-
E.
Dan Jinks
Dan Jinks is an American film and television producer best known for acclaimed movies such as "American Beauty" and "Big Fish."
- 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: Billy Jenkins Triple: [Jenkins, hasNotableBearer, Billy Jenkins]
Generated description
Billy Jenkins is a name shared by several notable individuals, including musicians and athletes, recognized within their respective fields.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Billy Jenkins Target entity description: Billy Jenkins is a name shared by several notable individuals, including musicians and athletes, recognized within their respective fields.
-
A.
Michael Jenkins
Michael Jenkins is a theatre producer best known for his work on the hit musical comedy "Spamalot."
-
B.
Michael Jenkins
Michael Jenkins is an Australian screenwriter and director known for his work in film and television, including influential Australian dramas.
-
C.
Allen Jenkins
Allen Jenkins was an American character actor known for his comic supporting roles in numerous Hollywood films of the 1930s and 1940s.
-
D.
Jeff Jenkins
Jeff Jenkins is a television producer best known for his work on reality TV series, particularly within the Kardashian franchise.
-
E.
Dan Jinks
Dan Jinks is an American film and television producer best known for acclaimed movies such as "American Beauty" and "Big Fish."
- 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_69c008cc158881908df6ec94a911c736 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c063c0629c8190805ddf1a604e9ca4 |
completed | March 22, 2026, 9:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c2446ad060819094acd817ba5eadc9 |
completed | March 24, 2026, 7:59 a.m. |
| NEDg | Description generation | batch_69c4fb6bb9bc8190a29ae09221aa5464 |
completed | March 26, 2026, 9:24 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c4fc075dd881908230bb66d1445d5a |
completed | March 26, 2026, 9:27 a.m. |
Created at: March 22, 2026, 4:25 p.m.