Triple
T22016366
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mendel Rosenblum |
E543720
|
entity |
| Predicate | coFounderWith |
P2835
|
FINISHED |
| Object | Edward Wang |
—
|
NE NERFINISHED |
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: Edward Wang | Statement: [Mendel Rosenblum, coFounderWith, Edward Wang]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Edward Wang Context triple: [Mendel Rosenblum, coFounderWith, Edward Wang]
-
A.
Edward Wang
chosen
Edward Wang is an entrepreneur best known as a founder of the virtualization and cloud computing company VMware.
-
B.
William Wang
William Wang is an entrepreneur best known as a co-founder of the social gaming company Playdom.
-
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.
Stephen Wang
Stephen Wang is an entrepreneur best known as a co-founder of the film and television review aggregation website Rotten Tomatoes.
-
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.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e2e8ea4819084210fe06d3a1b8d |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f127a8a1388190b9e0c1795fe1183a |
completed | April 28, 2026, 9:33 p.m. |
Created at: April 16, 2026, 8:23 p.m.