Triple
T19452603
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Teenage Bounty Hunters |
E486648
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object |
Bowser Jenkins
Bowser Jenkins is a central character in the Netflix dramedy "Teenage Bounty Hunters," serving as the experienced bounty hunter who mentors the twin teen protagonists.
|
E1377576
|
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: Bowser Jenkins | Statement: [Teenage Bounty Hunters, mainCharacter, Bowser Jenkins]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bowser Jenkins Context triple: [Teenage Bounty Hunters, mainCharacter, Bowser Jenkins]
-
A.
Mickey Knox
Mickey Knox is the violent, media-sensationalized serial killer protagonist from the film "Natural Born Killers."
-
B.
Buster Jones
Buster Jones was an American voice actor best known for his work in animated television series during the 1980s and 1990s.
-
C.
Paulie Bleeker
Paulie Bleeker is a shy, sweet-natured high school track athlete and the awkward love interest of the title character in the film "Juno."
-
D.
Handsome Bob
Handsome Bob is a stylish, soft-spoken gangster and member of One Two’s crew in Guy Ritchie’s crime film "RocknRolla."
-
E.
Booger McFarland
Booger McFarland is a former NFL defensive tackle who became a prominent American football television analyst and color commentator.
- 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: Bowser Jenkins Triple: [Teenage Bounty Hunters, mainCharacter, Bowser Jenkins]
Generated description
Bowser Jenkins is a central character in the Netflix dramedy "Teenage Bounty Hunters," serving as the experienced bounty hunter who mentors the twin teen protagonists.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bowser Jenkins Target entity description: Bowser Jenkins is a central character in the Netflix dramedy "Teenage Bounty Hunters," serving as the experienced bounty hunter who mentors the twin teen protagonists.
-
A.
Mickey Knox
Mickey Knox is the violent, media-sensationalized serial killer protagonist from the film "Natural Born Killers."
-
B.
Buster Jones
Buster Jones was an American voice actor best known for his work in animated television series during the 1980s and 1990s.
-
C.
Paulie Bleeker
Paulie Bleeker is a shy, sweet-natured high school track athlete and the awkward love interest of the title character in the film "Juno."
-
D.
Handsome Bob
Handsome Bob is a stylish, soft-spoken gangster and member of One Two’s crew in Guy Ritchie’s crime film "RocknRolla."
-
E.
Booger McFarland
Booger McFarland is a former NFL defensive tackle who became a prominent American football television analyst and color commentator.
- 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_69d8e8d86d608190bd199a98d0297f27 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63392aab08190aab09b7c356e5b10 |
completed | April 20, 2026, 2:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a073b33395081909ac7e5406843da5c |
completed | May 15, 2026, 3:26 p.m. |
| NEDg | Description generation | batch_6a073ba7f03481908ed5c06a46c0a029 |
completed | May 15, 2026, 3:28 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a073cae2df481908ed9a0ee0bc14fd5 |
completed | May 15, 2026, 3:33 p.m. |
Created at: April 10, 2026, 1:38 p.m.