Triple
T1737296
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 60 Minutes |
E37947
|
entity |
| Predicate | executiveProducer |
P7225
|
FINISHED |
| Object |
Jeff Fager
Jeff Fager is an American television producer best known for leading and shaping the long-running CBS news magazine program "60 Minutes."
|
E200398
|
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 Fager | Statement: [60 Minutes, executiveProducer, Jeff Fager]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jeff Fager Context triple: [60 Minutes, executiveProducer, Jeff Fager]
-
A.
John O’May
John O’May is an actor known for his role in the Australian musical comedy film "Starstruck" (1982).
-
B.
Mike Krieger
Mike Krieger is a Brazilian-American entrepreneur and software engineer best known as the co-founder and former CTO of the photo-sharing social media platform Instagram.
-
C.
Dan Foy
Dan Foy is an American local politician who serves as the mayor of Burbank, Illinois.
-
D.
Gary Melius
Gary Melius is an American real estate developer best known for owning and extensively restoring Oheka Castle, a historic Gold Coast mansion on Long Island.
-
E.
Mike Hunt
Mike Hunt is a name best known as a long-running prank or joke name in English-speaking popular culture due to its phonetic resemblance to a vulgar phrase.
- 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 Fager Triple: [60 Minutes, executiveProducer, Jeff Fager]
Generated description
Jeff Fager is an American television producer best known for leading and shaping the long-running CBS news magazine program "60 Minutes."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jeff Fager Target entity description: Jeff Fager is an American television producer best known for leading and shaping the long-running CBS news magazine program "60 Minutes."
-
A.
John O’May
John O’May is an actor known for his role in the Australian musical comedy film "Starstruck" (1982).
-
B.
Mike Krieger
Mike Krieger is a Brazilian-American entrepreneur and software engineer best known as the co-founder and former CTO of the photo-sharing social media platform Instagram.
-
C.
Dan Foy
Dan Foy is an American local politician who serves as the mayor of Burbank, Illinois.
-
D.
Gary Melius
Gary Melius is an American real estate developer best known for owning and extensively restoring Oheka Castle, a historic Gold Coast mansion on Long Island.
-
E.
Mike Hunt
Mike Hunt is a name best known as a long-running prank or joke name in English-speaking popular culture due to its phonetic resemblance to a vulgar phrase.
- 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_69a8861cc6ac8190ac0b2e31ccf62851 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa63a47cd481909c211e4da7f5dfe9 |
completed | March 6, 2026, 5:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adb5c065088190b831c65ae55eed14 |
completed | March 8, 2026, 5:45 p.m. |
| NEDg | Description generation | batch_69adb69b142c81909dd8bd40e8e440ad |
completed | March 8, 2026, 5:49 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69adb8bac99081908cf126d42c609559 |
completed | March 8, 2026, 5:58 p.m. |
Created at: March 4, 2026, 7:30 p.m.