Triple
T9289807
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Diego Seals |
E223487
|
entity |
| Predicate | owner |
P347
|
FINISHED |
| Object | Joseph Tsai |
E6674
|
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: Joseph Tsai | Statement: [San Diego Seals, owner, Joseph Tsai]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Joseph Tsai Context triple: [San Diego Seals, owner, Joseph Tsai]
-
A.
Joe Tsai
chosen
Joe Tsai is a Taiwanese-Canadian billionaire businessman and co-founder of Alibaba Group who owns the NBA’s Brooklyn Nets.
-
B.
Albert Tsai
Albert Tsai is an American child actor known for his comedic television roles, including his breakout performance on the sitcom "Trophy Wife."
-
C.
Tom Wu
Tom Wu is a British actor and martial artist known for his roles in action and crime films and television series.
-
D.
Mark Chen
Mark Chen is an AI researcher known for co-authoring influential work on large language models alongside Tom B. Brown at OpenAI.
-
E.
Stan Shih
Stan Shih is a Taiwanese entrepreneur and philanthropist best known as the co-founder and longtime leader of the multinational computer company Acer Inc.
- 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_69ca8422ddf881908a3f8f876c9f53aa |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd08643a848190a8b5be1ccc0b2ef6 |
completed | April 1, 2026, 11:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0b22ff5d881909ed5ac15ad8cbbb6 |
completed | April 4, 2026, 6:39 a.m. |
Created at: March 30, 2026, 7:35 p.m.