Triple
T15833958
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Andy Fang |
E383938
|
entity |
| Predicate | businessPartner |
P282
|
FINISHED |
| Object | Stanley Tang |
E387415
|
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: Stanley Tang | Statement: [Andy Fang, businessPartner, Stanley Tang]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stanley Tang Context triple: [Andy Fang, businessPartner, Stanley Tang]
-
A.
Stanley Tang
chosen
Stanley Tang is a technology entrepreneur best known as a co-founder of the food delivery platform DoorDash.
-
B.
Alfred Chuang
Alfred Chuang is a Chinese-American technology entrepreneur best known as the co-founder and former CEO of enterprise software company BEA Systems.
-
C.
Charles Lai
Charles Lai is a community leader and cultural advocate best known for co-founding the Museum of Chinese in America, which preserves and presents the history and experiences of Chinese Americans.
-
D.
Lawrence Chu
Lawrence Chu is a Chinese-American chef and restaurateur best known as the father of film director Jon M. Chu.
-
E.
Russell Wong
Russell Wong is an American actor and martial artist best known for his roles in action films and television series, often portraying skilled fighters or law enforcement characters.
- 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_69d86da34c888190976e06c4019d415a |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e11e6670d48190a456581dd951f168 |
completed | April 16, 2026, 5:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffa93be478819099908e7242f532d7 |
completed | May 9, 2026, 9:38 p.m. |
Created at: April 10, 2026, 4:49 a.m.