Triple
T4975626
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | He (surname) |
E111757
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
He Kexin
He Kexin is a Chinese artistic gymnast best known for winning multiple Olympic gold medals on the uneven bars.
|
E484686
|
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: He Kexin | Statement: [He (surname), hasNotableBearer, He Kexin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: He Kexin Context triple: [He (surname), hasNotableBearer, He Kexin]
-
A.
Xue Yue
Xue Yue was a prominent Nationalist Chinese general renowned for his leadership in key battles against Japanese forces during the Second Sino-Japanese War.
-
B.
Xiao Ke
Xiao Ke was a prominent Chinese military leader and general of the People’s Liberation Army who played key roles in the Chinese Civil War and early PRC military development.
-
C.
Li Jingxi
Li Jingxi was a Chinese politician and statesman who briefly served as premier during the early years of the Republic of China.
-
D.
Xie Lian
Xie Lian was the wife of Chinese Communist military leader and Marshal Liu Bocheng.
-
E.
Jun Xia
Jun Xia is a Chinese architect best known for serving as the lead designer of Shanghai Tower, one of the world’s tallest skyscrapers.
- 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: He Kexin Triple: [He (surname), hasNotableBearer, He Kexin]
Generated description
He Kexin is a Chinese artistic gymnast best known for winning multiple Olympic gold medals on the uneven bars.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: He Kexin Target entity description: He Kexin is a Chinese artistic gymnast best known for winning multiple Olympic gold medals on the uneven bars.
-
A.
Xue Yue
Xue Yue was a prominent Nationalist Chinese general renowned for his leadership in key battles against Japanese forces during the Second Sino-Japanese War.
-
B.
Xiao Ke
Xiao Ke was a prominent Chinese military leader and general of the People’s Liberation Army who played key roles in the Chinese Civil War and early PRC military development.
-
C.
Li Jingxi
Li Jingxi was a Chinese politician and statesman who briefly served as premier during the early years of the Republic of China.
-
D.
Xie Lian
Xie Lian was the wife of Chinese Communist military leader and Marshal Liu Bocheng.
-
E.
Jun Xia
Jun Xia is a Chinese architect best known for serving as the lead designer of Shanghai Tower, one of the world’s tallest skyscrapers.
- 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_69bd441a0eb481908050fa4273b19eae |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd7230086c81909c045614721bd89f |
completed | March 20, 2026, 4:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be8a01e548819087e3a6ae2cd581b9 |
completed | March 21, 2026, 12:07 p.m. |
| NEDg | Description generation | batch_69be8c193f2c8190a220ffc2571bcb64 |
completed | March 21, 2026, 12:16 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69be8c6723f08190b0e722dbb1171173 |
completed | March 21, 2026, 12:17 p.m. |
Created at: March 20, 2026, 1:33 p.m.