Triple
T5277933
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VMware |
E119418
|
entity |
| Predicate | foundedBy |
P104
|
FINISHED |
| Object |
Edward Wang
Edward Wang is an entrepreneur best known as a founder of the virtualization and cloud computing company VMware.
|
E509079
|
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: Edward Wang | Statement: [VMware, foundedBy, Edward Wang]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Edward Wang Context triple: [VMware, foundedBy, Edward 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.
Jonathan Wang
Jonathan Wang is a film producer best known for his work on the acclaimed, genre-bending movie "Everything Everywhere All at Once."
-
C.
Waymond Wang
Waymond Wang is a gentle, optimistic husband and father whose unexpected resilience and kindness play a crucial role in the multiverse-spanning story of the film "Everything Everywhere All at Once."
-
D.
John Cheng
John Cheng is a film producer best known for his work on the dark comedy movie "Horrible Bosses."
-
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: Edward Wang Triple: [VMware, foundedBy, Edward Wang]
Generated description
Edward Wang is an entrepreneur best known as a founder of the virtualization and cloud computing company VMware.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Edward Wang Target entity description: Edward Wang is an entrepreneur best known as a founder of the virtualization and cloud computing company VMware.
-
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.
Jonathan Wang
Jonathan Wang is a film producer best known for his work on the acclaimed, genre-bending movie "Everything Everywhere All at Once."
-
C.
Waymond Wang
Waymond Wang is a gentle, optimistic husband and father whose unexpected resilience and kindness play a crucial role in the multiverse-spanning story of the film "Everything Everywhere All at Once."
-
D.
John Cheng
John Cheng is a film producer best known for his work on the dark comedy movie "Horrible Bosses."
-
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_69bd446d05a8819092ad333a3f9c8d5c |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd8474e7fc8190ab5dd84f665ae6a4 |
completed | March 20, 2026, 5:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf06d9aab08190ad9905925a849922 |
completed | March 21, 2026, 9 p.m. |
| NEDg | Description generation | batch_69bf0940d79081909d0f87359df5100f |
completed | March 21, 2026, 9:10 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69bf0999f36c8190bb707c27228690f7 |
completed | March 21, 2026, 9:11 p.m. |
Created at: March 20, 2026, 1:51 p.m.