Triple
T15507044
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William Wang |
E379108
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | Vizio |
E77119
|
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: Vizio | Statement: [William Wang, employer, Vizio]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vizio Context triple: [William Wang, employer, Vizio]
-
A.
Vizio
chosen
Vizio is an American consumer electronics company best known for its affordable flat-screen televisions and home entertainment products.
-
B.
Toshiba REGZA
Toshiba REGZA is a line of high-definition televisions and display devices produced by Toshiba, known for their advanced picture processing and multimedia features.
-
C.
Bravia
Bravia is Sony's line of high-definition televisions and display products known for their advanced picture and sound technologies.
-
D.
Panasonic Viera TV
Panasonic Viera TV is a line of high-definition televisions by Panasonic known for integrating advanced picture technology with smart connectivity and home theater features.
-
E.
Paramount Vantage
Paramount Vantage was a specialty film division of Paramount Pictures focused on producing and distributing independent, art-house, and prestige films.
- 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_69ff366e472c819093472da2a49593c6 |
completed | May 9, 2026, 1:28 p.m. |
Created at: April 10, 2026, 3:55 a.m.