Triple
T19872312
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Number One with a Bullet |
E477547
|
entity |
| Predicate | hasCastMember |
P2308
|
FINISHED |
| Object |
Michael Paul Chan
Michael Paul Chan is an American character actor best known for his roles in film and television series such as "The Closer" and "Major Crimes."
|
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 Paul Chan | Statement: [Number One with a Bullet, hasCastMember, Michael Paul Chan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Paul Chan Context triple: [Number One with a Bullet, hasCastMember, Michael Paul Chan]
-
A.
Michael Chan
Michael Chan is a common personal name shared by multiple individuals across fields such as politics, business, and entertainment.
-
B.
Ryan Chan
Ryan Chan is a film editor known for his work on the 2020 adaptation of "The Witches."
-
C.
Matthew Chuang
Matthew Chuang is a cinematographer known for his visually distinctive work on the film "Blue Bayou."
-
D.
Daniel James Chan
Daniel James Chan is a television and film composer best known for scoring the superhero series "DC's Legends of Tomorrow."
-
E.
Phillip Chan
Phillip Chan is a Hong Kong actor known for appearing in action and martial arts films, including collaborations with major stars of the territory’s cinema.
- 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 Paul Chan Triple: [Number One with a Bullet, hasCastMember, Michael Paul Chan]
Generated description
Michael Paul Chan is an American character actor best known for his roles in film and television series such as "The Closer" and "Major Crimes."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Michael Paul Chan Target entity description: Michael Paul Chan is an American character actor best known for his roles in film and television series such as "The Closer" and "Major Crimes."
-
A.
Michael Chan
chosen
Michael Chan is a common personal name shared by multiple individuals across fields such as politics, business, and entertainment.
-
B.
Ryan Chan
Ryan Chan is a film editor known for his work on the 2020 adaptation of "The Witches."
-
C.
Matthew Chuang
Matthew Chuang is a cinematographer known for his visually distinctive work on the film "Blue Bayou."
-
D.
Daniel James Chan
Daniel James Chan is a television and film composer best known for scoring the superhero series "DC's Legends of Tomorrow."
-
E.
Phillip Chan
Phillip Chan is a Hong Kong actor known for appearing in action and martial arts films, including collaborations with major stars of the territory’s cinema.
- F. None of above.
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_69d8e51e7d948190aedbcd6c30361c39 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e658d826f88190be04188997952d1b |
completed | April 20, 2026, 4:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a07dbc44f748190a65d88890960d90b |
completed | May 16, 2026, 2:51 a.m. |
| NEDg | Description generation | batch_6a07dc854a0c8190b0da81ead6b9cfc1 |
completed | May 16, 2026, 2:55 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a07dd45e93c8190b14c23487398a8ec |
completed | May 16, 2026, 2:58 a.m. |
Created at: April 10, 2026, 1:51 p.m.