Triple
T7724267
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ma Lin |
E175089
|
entity |
| Predicate | nativeName |
P15
|
FINISHED |
| Object |
马琳
马琳是一位中国著名乒乓球运动员和教练,曾多次获得奥运会和世锦赛冠军。
|
E684457
|
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: 马琳 | Statement: [Ma Lin, nativeName, 马琳]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 马琳 Context triple: [Ma Lin, nativeName, 马琳]
-
A.
Chen Xiangmei
Chen Xiangmei, better known as Anna Chennault, was a prominent Chinese-American journalist, Republican political operative, and influential figure in U.S.–China relations during the Cold War.
-
B.
Yang Jinyu
Yang Jinyu was a Chinese military figure and graduate of the Yunnan Military Academy who became notable for his role in early 20th-century Chinese military and political affairs.
-
C.
Wu Minxia
Wu Minxia is a Chinese diver and multiple Olympic gold medalist renowned for her dominance in synchronized and springboard diving events.
-
D.
Guo Jingjing
Guo Jingjing is a retired Chinese diver, widely regarded as one of the greatest female springboard divers in history and a multiple Olympic and world champion.
-
E.
Zhang Huiwen
Zhang Huiwen is a Chinese actress best known for her breakout role in Zhang Yimou’s film "Coming Home," which brought her widespread recognition.
- 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: 马琳 Triple: [Ma Lin, nativeName, 马琳]
Generated description
马琳是一位中国著名乒乓球运动员和教练,曾多次获得奥运会和世锦赛冠军。
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: 马琳 Target entity description: 马琳是一位中国著名乒乓球运动员和教练,曾多次获得奥运会和世锦赛冠军。
-
A.
Chen Xiangmei
Chen Xiangmei, better known as Anna Chennault, was a prominent Chinese-American journalist, Republican political operative, and influential figure in U.S.–China relations during the Cold War.
-
B.
Yang Jinyu
Yang Jinyu was a Chinese military figure and graduate of the Yunnan Military Academy who became notable for his role in early 20th-century Chinese military and political affairs.
-
C.
Wu Minxia
Wu Minxia is a Chinese diver and multiple Olympic gold medalist renowned for her dominance in synchronized and springboard diving events.
-
D.
Guo Jingjing
Guo Jingjing is a retired Chinese diver, widely regarded as one of the greatest female springboard divers in history and a multiple Olympic and world champion.
-
E.
Zhang Huiwen
Zhang Huiwen is a Chinese actress best known for her breakout role in Zhang Yimou’s film "Coming Home," which brought her widespread recognition.
- 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_69c6995d541c81909eaa646b1a8369a9 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7031279708190a3a5fb64f9206974 |
completed | March 27, 2026, 10:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8b51faa348190b4fa0b5a307c83db |
completed | March 29, 2026, 5:14 a.m. |
| NEDg | Description generation | batch_69c8b74ee6d081908454b2d4774a3a7b |
completed | March 29, 2026, 5:23 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c8b7af4c58819097360e89e7ea6062 |
completed | March 29, 2026, 5:25 a.m. |
Created at: March 27, 2026, 4:05 p.m.