Triple
T15507065
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vizio |
E379108
|
entity |
| Predicate | keyPerson |
P256
|
FINISHED |
| Object | William Wang |
E379108
|
NE FINISHED |
How this triple was built (2 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: William Wang | Statement: [Vizio, keyPerson, William Wang]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: William Wang Context triple: [Vizio, keyPerson, William Wang]
-
A.
William Wang
chosen
William Wang is a Taiwanese-American entrepreneur best known as the founder and longtime CEO of the consumer electronics company Vizio.
-
B.
Edward Wang
Edward Wang is an entrepreneur best known as a founder of the virtualization and cloud computing company VMware.
-
C.
Ben Wang
Ben Wang is an actor best known for playing the lead role of Jin Wang in the television adaptation of "American Born Chinese."
-
D.
Jonathan Wang
Jonathan Wang is a film producer best known for his work on the acclaimed, genre-bending movie "Everything Everywhere All at Once."
-
E.
William Li
William Li is a Chinese entrepreneur best known as the founder and CEO of the electric vehicle company NIO.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d85cd53a7c819080f5b9042c4c199e |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03fcea8888190a7b69aca360183c3 |
completed | April 16, 2026, 1:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff454ca0f0819088ba846a448dda2e |
completed | May 9, 2026, 2:31 p.m. |
Created at: April 10, 2026, 3:55 a.m.