Triple
T3776714
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kourtney and Kim Take New York |
E83324
|
entity |
| Predicate | executiveProducer |
P7225
|
FINISHED |
| Object |
Jeff Jenkins
Jeff Jenkins is a television producer best known for his work on reality TV series, particularly within the Kardashian franchise.
|
E422730
|
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: Jeff Jenkins | Statement: [Kourtney and Kim Take New York, executiveProducer, Jeff Jenkins]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jeff Jenkins Context triple: [Kourtney and Kim Take New York, executiveProducer, Jeff Jenkins]
-
A.
Michael Jenkins
Michael Jenkins is an Australian screenwriter and director known for his work in film and television, including influential Australian dramas.
-
B.
Dan Jinks
Dan Jinks is an American film and television producer best known for acclaimed movies such as "American Beauty" and "Big Fish."
-
C.
Matthew Jensen
Matthew Jensen is a cinematographer best known for his work on major films such as the 2017 superhero movie "Wonder Woman."
-
D.
Jeff Gourson
Jeff Gourson is a film editor known for his work on movies such as the comedy "White Chicks."
-
E.
Chris Weinke
Chris Weinke is a former American football quarterback best known for leading Florida State University to a national championship and winning the Heisman Trophy before playing in the NFL.
- 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: Jeff Jenkins Triple: [Kourtney and Kim Take New York, executiveProducer, Jeff Jenkins]
Generated description
Jeff Jenkins is a television producer best known for his work on reality TV series, particularly within the Kardashian franchise.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jeff Jenkins Target entity description: Jeff Jenkins is a television producer best known for his work on reality TV series, particularly within the Kardashian franchise.
-
A.
Michael Jenkins
Michael Jenkins is an Australian screenwriter and director known for his work in film and television, including influential Australian dramas.
-
B.
Dan Jinks
Dan Jinks is an American film and television producer best known for acclaimed movies such as "American Beauty" and "Big Fish."
-
C.
Matthew Jensen
Matthew Jensen is a cinematographer best known for his work on major films such as the 2017 superhero movie "Wonder Woman."
-
D.
Jeff Gourson
Jeff Gourson is a film editor known for his work on movies such as the comedy "White Chicks."
-
E.
Chris Weinke
Chris Weinke is a former American football quarterback best known for leading Florida State University to a national championship and winning the Heisman Trophy before playing in the NFL.
- 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_69ad8b235e608190b5a2b1d1bfcef50b |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcc5be3c48190a72e840d8214bb74 |
completed | March 8, 2026, 7:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b595eea03c8190a76a4e09a6d03919 |
completed | March 14, 2026, 5:07 p.m. |
| NEDg | Description generation | batch_69b599c94ce48190a77065377e7c09f3 |
completed | March 14, 2026, 5:24 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b59a2683488190954d95bc2f2bf456 |
completed | March 14, 2026, 5:25 p.m. |
Created at: March 8, 2026, 3:36 p.m.