Triple
T8700274
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ASUS |
E206511
|
entity |
| Predicate | foundedBy |
P104
|
FINISHED |
| Object |
Ted Hsu
Ted Hsu is a Taiwanese entrepreneur best known as one of the co-founders of the technology company ASUS.
|
E750955
|
NE FINISHED |
How this triple was built (4 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: Ted Hsu | Statement: [ASUS, foundedBy, Ted Hsu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ted Hsu Context triple: [ASUS, foundedBy, Ted Hsu]
-
A.
Roger Yuan
Roger Yuan is an American martial artist, fight choreographer, and actor known for his roles and stunt work in numerous action films.
-
B.
James Hong
James Hong is a prolific American character actor and voice actor known for his roles in films like "Big Trouble in Little China," "Blade Runner," and numerous animated features.
-
C.
Eddie Wu
Eddie Wu is a Chinese entrepreneur and technology executive best known as a co-founder and later CEO of Alibaba Group.
-
D.
Daniel Wu
Daniel Wu is a Hong Kong-American actor, director, and producer known for his roles in action and fantasy films as well as the TV series "Into the Badlands."
-
E.
Eric Tsang
Eric Tsang is a veteran Hong Kong actor, comedian, and film producer known for his prolific career in Cantonese cinema and television.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Ted Hsu Triple: [ASUS, foundedBy, Ted Hsu]
Generated description
Ted Hsu is a Taiwanese entrepreneur best known as one of the co-founders of the technology company ASUS.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ted Hsu Target entity description: Ted Hsu is a Taiwanese entrepreneur best known as one of the co-founders of the technology company ASUS.
-
A.
Roger Yuan
Roger Yuan is an American martial artist, fight choreographer, and actor known for his roles and stunt work in numerous action films.
-
B.
James Hong
James Hong is a prolific American character actor and voice actor known for his roles in films like "Big Trouble in Little China," "Blade Runner," and numerous animated features.
-
C.
Eddie Wu
Eddie Wu is a Chinese entrepreneur and technology executive best known as a co-founder and later CEO of Alibaba Group.
-
D.
Daniel Wu
Daniel Wu is a Hong Kong-American actor, director, and producer known for his roles in action and fantasy films as well as the TV series "Into the Badlands."
-
E.
Eric Tsang
Eric Tsang is a veteran Hong Kong actor, comedian, and film producer known for his prolific career in Cantonese cinema and television.
- F. None of above. chosen
Provenance (5 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_69ca83555b6c8190abe930dd397e863b |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc58b27bd48190a5f76111ee657553 |
completed | March 31, 2026, 11:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cef40e7a2881909e2d7eee0d931992 |
completed | April 2, 2026, 10:56 p.m. |
| NEDg | Description generation | batch_69cef66624348190b1f922b8148553a2 |
completed | April 2, 2026, 11:06 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cef6d9ea7c81909dfefb8540636092 |
completed | April 2, 2026, 11:08 p.m. |
Created at: March 30, 2026, 6:34 p.m.