Triple
T3993252
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Everything Everywhere All at Once |
E87040
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object |
Jonathan Wang
Jonathan Wang is a film producer best known for his work on the acclaimed, genre-bending movie "Everything Everywhere All at Once."
|
E407106
|
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: Jonathan Wang | Statement: [Everything Everywhere All at Once, producer, Jonathan Wang]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jonathan Wang Context triple: [Everything Everywhere All at Once, producer, Jonathan Wang]
-
A.
William Wang
William Wang is a Taiwanese-American entrepreneur best known as the founder and longtime CEO of the consumer electronics company Vizio.
-
B.
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."
-
C.
Daniel Zhang
Daniel Zhang is a Chinese business executive best known for leading Alibaba Group through a major period of global expansion and for creating the Singles’ Day shopping festival.
-
D.
James Zhou
James Zhou is a Chinese businessman best known as the owner and chairman of French football club AJ Auxerre.
-
E.
John Cheng
John Cheng is a film producer best known for his work on the dark comedy movie "Horrible Bosses."
- 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: Jonathan Wang Triple: [Everything Everywhere All at Once, producer, Jonathan Wang]
Generated description
Jonathan Wang is a film producer best known for his work on the acclaimed, genre-bending movie "Everything Everywhere All at Once."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jonathan Wang Target entity description: Jonathan Wang is a film producer best known for his work on the acclaimed, genre-bending movie "Everything Everywhere All at Once."
-
A.
William Wang
William Wang is a Taiwanese-American entrepreneur best known as the founder and longtime CEO of the consumer electronics company Vizio.
-
B.
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."
-
C.
Daniel Zhang
Daniel Zhang is a Chinese business executive best known for leading Alibaba Group through a major period of global expansion and for creating the Singles’ Day shopping festival.
-
D.
James Zhou
James Zhou is a Chinese businessman best known as the owner and chairman of French football club AJ Auxerre.
-
E.
John Cheng
John Cheng is a film producer best known for his work on the dark comedy movie "Horrible Bosses."
- 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_69aed94118148190975e6aa4e554cde9 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefa1d9d8c8190982d092a73d38564 |
completed | March 9, 2026, 4:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b54c50f348819090ebfd8b5192c819 |
completed | March 14, 2026, 11:53 a.m. |
| NEDg | Description generation | batch_69b550142cb88190b797ea327cff136e |
completed | March 14, 2026, 12:09 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5507641408190ab3407faf0aee807 |
completed | March 14, 2026, 12:11 p.m. |
Created at: March 9, 2026, 3:33 p.m.