Triple
T6126263
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joy |
E136603
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object |
Ken Mok
Ken Mok is a television and film producer best known for creating and executive producing the reality competition series "America's Next Top Model."
|
E571342
|
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: Ken Mok | Statement: [Joy, producer, Ken Mok]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ken Mok Context triple: [Joy, producer, Ken Mok]
-
A.
Donald Tsang
Donald Tsang is a Hong Kong politician who served as the second Chief Executive of Hong Kong from 2005 to 2012.
-
B.
Stanley Tang
Stanley Tang is a technology entrepreneur best known as a co-founder of the food delivery platform DoorDash.
-
C.
Ronald Cheng
Ronald Cheng is a Hong Kong actor and Cantopop singer known for his comedic film roles and successful music career.
-
D.
Chan Kwong-wing
Chan Kwong-wing is a Hong Kong film composer best known for his scores for acclaimed movies such as the Infernal Affairs trilogy.
-
E.
Gerald Chan
Gerald Chan is a Hong Kong-born American billionaire investor and philanthropist known for major donations to Harvard University and leadership of the Morningside Group.
- 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: Ken Mok Triple: [Joy, producer, Ken Mok]
Generated description
Ken Mok is a television and film producer best known for creating and executive producing the reality competition series "America's Next Top Model."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ken Mok Target entity description: Ken Mok is a television and film producer best known for creating and executive producing the reality competition series "America's Next Top Model."
-
A.
Donald Tsang
Donald Tsang is a Hong Kong politician who served as the second Chief Executive of Hong Kong from 2005 to 2012.
-
B.
Stanley Tang
Stanley Tang is a technology entrepreneur best known as a co-founder of the food delivery platform DoorDash.
-
C.
Ronald Cheng
Ronald Cheng is a Hong Kong actor and Cantopop singer known for his comedic film roles and successful music career.
-
D.
Chan Kwong-wing
Chan Kwong-wing is a Hong Kong film composer best known for his scores for acclaimed movies such as the Infernal Affairs trilogy.
-
E.
Gerald Chan
Gerald Chan is a Hong Kong-born American billionaire investor and philanthropist known for major donations to Harvard University and leadership of the Morningside Group.
- 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_69c008a0a37c81908e5b4f879158afb3 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c05c28dbbc8190a0a0c20ec794e81a |
completed | March 22, 2026, 9:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c135bd8d3881909873d2a063b3aecc |
completed | March 23, 2026, 12:44 p.m. |
| NEDg | Description generation | batch_69c1392b0e448190846ccf73e89a6ad3 |
completed | March 23, 2026, 12:59 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c139884ba881908db94f17d8d97faf |
completed | March 23, 2026, 1 p.m. |
Created at: March 22, 2026, 4:15 p.m.