Triple
T1524333
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ma |
E32300
|
entity |
| Predicate | notableBearer |
P458
|
FINISHED |
| Object |
Ma Sichun
Ma Sichun is a Chinese actress known for her acclaimed film and television roles, including winning the Golden Horse Award for Best Leading Actress.
|
E179087
|
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: Ma Sichun | Statement: [Ma, notableBearer, Ma Sichun]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ma Sichun Context triple: [Ma, notableBearer, Ma Sichun]
-
A.
Ma Sicong
Ma Sicong was a prominent 20th-century Chinese violinist and composer known for integrating Western classical techniques with Chinese musical elements.
-
B.
Sun Lianzhong
Sun Lianzhong was a Nationalist Chinese general noted for his leadership in key battles against Japanese forces during the Second Sino-Japanese War.
-
C.
Xuan
Xuan is a Vietnamese surname commonly used as a family name in Vietnam.
-
D.
Shan Zuchang
Shan Zuchang is a Chinese businessman best known for serving as chairman of English football club West Bromwich Albion.
-
E.
Shaoshan
Shaoshan is a town in Hunan Province, China, best known as the birthplace of Mao Zedong and a significant site of modern Chinese revolutionary history.
- 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: Ma Sichun Triple: [Ma, notableBearer, Ma Sichun]
Generated description
Ma Sichun is a Chinese actress known for her acclaimed film and television roles, including winning the Golden Horse Award for Best Leading Actress.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ma Sichun Target entity description: Ma Sichun is a Chinese actress known for her acclaimed film and television roles, including winning the Golden Horse Award for Best Leading Actress.
-
A.
Ma Sicong
Ma Sicong was a prominent 20th-century Chinese violinist and composer known for integrating Western classical techniques with Chinese musical elements.
-
B.
Sun Lianzhong
Sun Lianzhong was a Nationalist Chinese general noted for his leadership in key battles against Japanese forces during the Second Sino-Japanese War.
-
C.
Xuan
Xuan is a Vietnamese surname commonly used as a family name in Vietnam.
-
D.
Shan Zuchang
Shan Zuchang is a Chinese businessman best known for serving as chairman of English football club West Bromwich Albion.
-
E.
Shaoshan
Shaoshan is a town in Hunan Province, China, best known as the birthplace of Mao Zedong and a significant site of modern Chinese revolutionary history.
- 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_69a885e9b0ac819093a9806ad0efc82c |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a9080175588190bb3b1d4b17966f2f |
completed | March 5, 2026, 4:35 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad401616ec81908edd9dcb9f4a0184 |
completed | March 8, 2026, 9:23 a.m. |
| NEDg | Description generation | batch_69ad4130bf30819092be42a4e9225220 |
completed | March 8, 2026, 9:28 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad41968e4c8190b843b97e18ac9968 |
completed | March 8, 2026, 9:29 a.m. |
Created at: March 4, 2026, 7:26 p.m.