Triple
T5693590
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Wedding Banquet |
E125482
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object |
Neil Peng
Neil Peng is a Taiwanese screenwriter best known for co-writing Ang Lee’s acclaimed film "The Wedding Banquet."
|
E539310
|
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: Neil Peng | Statement: [The Wedding Banquet, screenwriter, Neil Peng]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Neil Peng Context triple: [The Wedding Banquet, screenwriter, Neil Peng]
-
A.
John Cheng
John Cheng is a film producer best known for his work on the dark comedy movie "Horrible Bosses."
-
B.
Sean Chen
Sean Chen is a Taiwanese politician and technocrat who served as Premier of the Republic of China (Taiwan) in the early 2010s, known for his background in finance and economic policy.
-
C.
William Wang
William Wang is a Taiwanese-American entrepreneur best known as the founder and longtime CEO of the consumer electronics company Vizio.
-
D.
Eddie Peng
Eddie Peng is a Taiwanese-Canadian actor and singer known for his roles in Chinese-language action and historical films.
-
E.
Jonathan Wang
Jonathan Wang is a film producer best known for his work on the acclaimed, genre-bending movie "Everything Everywhere All at Once."
- 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: Neil Peng Triple: [The Wedding Banquet, screenwriter, Neil Peng]
Generated description
Neil Peng is a Taiwanese screenwriter best known for co-writing Ang Lee’s acclaimed film "The Wedding Banquet."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Neil Peng Target entity description: Neil Peng is a Taiwanese screenwriter best known for co-writing Ang Lee’s acclaimed film "The Wedding Banquet."
-
A.
John Cheng
John Cheng is a film producer best known for his work on the dark comedy movie "Horrible Bosses."
-
B.
Sean Chen
Sean Chen is a Taiwanese politician and technocrat who served as Premier of the Republic of China (Taiwan) in the early 2010s, known for his background in finance and economic policy.
-
C.
William Wang
William Wang is a Taiwanese-American entrepreneur best known as the founder and longtime CEO of the consumer electronics company Vizio.
-
D.
Eddie Peng
Eddie Peng is a Taiwanese-Canadian actor and singer known for his roles in Chinese-language action and historical films.
-
E.
Jonathan Wang
Jonathan Wang is a film producer best known for his work on the acclaimed, genre-bending movie "Everything Everywhere All at Once."
- 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_69c0082bb19c8190823a4facd3cba79b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c023e7dbe48190850b501f223614e3 |
completed | March 22, 2026, 5:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c05a4f2bfc8190bc56c094f9ae9ce1 |
completed | March 22, 2026, 9:08 p.m. |
| NEDg | Description generation | batch_69c05bb76a748190a3b1a289dbd92dee |
completed | March 22, 2026, 9:14 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c05c498c4c8190bfa3ac17fba2b152 |
completed | March 22, 2026, 9:16 p.m. |
Created at: March 22, 2026, 3:44 p.m.