Triple
T19839718
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fu |
E476693
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Fu Haifeng
Fu Haifeng is a retired Chinese badminton player renowned as one of the greatest men's doubles specialists, winning multiple World Championships and Olympic gold medals.
|
E1478189
|
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: Fu Haifeng | Statement: [Fu, hasNotableBearer, Fu Haifeng]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fu Haifeng Context triple: [Fu, hasNotableBearer, Fu Haifeng]
-
A.
Chi Yufeng
Chi Yufeng is a Chinese entrepreneur best known as the founder of the entertainment and gaming company Perfect World Co., Ltd.
-
B.
He Jianfeng
He Jianfeng is a Chinese entrepreneur and art patron best known as the founder of the contemporary art institution He Art Museum.
-
C.
Li Feng
Li Feng is a Chinese screenwriter best known for co-writing the acclaimed wuxia film "House of Flying Daggers."
-
D.
Gao Xiaoheng
Gao Xiaoheng was a member of the House of Gao, a noble family associated with imperial rule in Chinese history.
-
E.
Su Zifeng
Su Zifeng is the birth name of Lisa Su, the Taiwanese-American electrical engineer and business executive who is the CEO of Advanced Micro Devices (AMD).
- 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: Fu Haifeng Triple: [Fu, hasNotableBearer, Fu Haifeng]
Generated description
Fu Haifeng is a retired Chinese badminton player renowned as one of the greatest men's doubles specialists, winning multiple World Championships and Olympic gold medals.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Fu Haifeng Target entity description: Fu Haifeng is a retired Chinese badminton player renowned as one of the greatest men's doubles specialists, winning multiple World Championships and Olympic gold medals.
-
A.
Chi Yufeng
Chi Yufeng is a Chinese entrepreneur best known as the founder of the entertainment and gaming company Perfect World Co., Ltd.
-
B.
He Jianfeng
He Jianfeng is a Chinese entrepreneur and art patron best known as the founder of the contemporary art institution He Art Museum.
-
C.
Li Feng
Li Feng is a Chinese screenwriter best known for co-writing the acclaimed wuxia film "House of Flying Daggers."
-
D.
Gao Xiaoheng
Gao Xiaoheng was a member of the House of Gao, a noble family associated with imperial rule in Chinese history.
-
E.
Su Zifeng
Su Zifeng is the birth name of Lisa Su, the Taiwanese-American electrical engineer and business executive who is the CEO of Advanced Micro Devices (AMD).
- 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_69d8e51d39d081909bcfafeaaf3d2fcc |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65804be608190b49e110c3bf381bc |
completed | April 20, 2026, 4:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a09a5a0922081909d31e5387fab9307 |
completed | May 17, 2026, 11:25 a.m. |
| NEDg | Description generation | batch_6a09a661daf48190a8a185395e334470 |
completed | May 17, 2026, 11:28 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a09a6ba6dfc8190841f4b254acf5a4d |
completed | May 17, 2026, 11:30 a.m. |
Created at: April 10, 2026, 1:50 p.m.