Triple
T735504
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chan |
E14920
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Michael Chan
Michael Chan is a common personal name shared by multiple individuals across fields such as politics, business, and entertainment.
|
E99894
|
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: Michael Chan | Statement: [Chan, hasNotableBearer, Michael Chan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Chan Context triple: [Chan, hasNotableBearer, Michael Chan]
-
A.
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.
-
B.
John Cheng
John Cheng is a film producer best known for his work on the dark comedy movie "Horrible Bosses."
-
C.
Jason Wong
Jason Wong is a British actor known for his roles in film and television, including his appearance in Guy Ritchie's crime-comedy series "The Gentlemen."
-
D.
Tony Wu
Tony Wu is a member of the technical team at xAI, the artificial intelligence company founded by Elon Musk.
-
E.
Victor Wong
Victor Wong was an American character actor known for his distinctive presence in films such as "The Last Emperor," "Big Trouble in Little China," and "Tremors."
- 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: Michael Chan Triple: [Chan, hasNotableBearer, Michael Chan]
Generated description
Michael Chan is a common personal name shared by multiple individuals across fields such as politics, business, and entertainment.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Michael Chan Target entity description: Michael Chan is a common personal name shared by multiple individuals across fields such as politics, business, and entertainment.
-
A.
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.
-
B.
John Cheng
John Cheng is a film producer best known for his work on the dark comedy movie "Horrible Bosses."
-
C.
Jason Wong
Jason Wong is a British actor known for his roles in film and television, including his appearance in Guy Ritchie's crime-comedy series "The Gentlemen."
-
D.
Tony Wu
Tony Wu is a member of the technical team at xAI, the artificial intelligence company founded by Elon Musk.
-
E.
Victor Wong
Victor Wong was an American character actor known for his distinctive presence in films such as "The Last Emperor," "Big Trouble in Little China," and "Tremors."
- 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_69a4934d9930819099eed80096b0597d |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a5da30b88190afbd12ae6109cc1b |
completed | March 1, 2026, 8:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a79280fa5c819098397cc1b5c626c0 |
completed | March 4, 2026, 2:01 a.m. |
| NEDg | Description generation | batch_69a79329fc2c81908dbf0627686ef47e |
completed | March 4, 2026, 2:04 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a793b89e38819090fd80afbb0fee96 |
completed | March 4, 2026, 2:06 a.m. |
Created at: March 1, 2026, 7:37 p.m.