Triple
T9614531
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yuan Zheng |
E232185
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Eric Yuan |
E45913
|
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: Eric Yuan | Statement: [Yuan Zheng, alsoKnownAs, Eric Yuan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eric Yuan Context triple: [Yuan Zheng, alsoKnownAs, Eric Yuan]
-
A.
Eric Yuan
chosen
Eric Yuan is a Chinese-American entrepreneur and software engineer best known as the founder and CEO of Zoom Video Communications, a leading video-conferencing platform.
-
B.
Mark Chen
Mark Chen is an AI researcher known for co-authoring influential work on large language models alongside Tom B. Brown at OpenAI.
-
C.
Ren Zhengfei
Ren Zhengfei is a Chinese entrepreneur best known as the founder and longtime leader of the telecommunications giant Huawei Technologies.
-
D.
Greg Zeschuk
Greg Zeschuk is a Canadian video game developer and physician best known as a co-founder of the acclaimed role-playing game studio BioWare.
-
E.
Anthony Hsieh
Anthony Hsieh is an American entrepreneur best known as the founder and former CEO of loanDepot, one of the largest nonbank mortgage lenders in the United States.
- 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_69ca84867bb88190b4b57dd5a56d5691 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9aaaa47881908d69381d4d11f49b |
completed | April 1, 2026, 10:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d17958287081908e337bdbe9ea366f |
completed | April 4, 2026, 8:49 p.m. |
Created at: March 30, 2026, 8:09 p.m.