Triple
T2312101
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peng |
E51981
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Peng Huanwu
Peng Huanwu was a prominent Chinese theoretical physicist known for his contributions to nuclear and particle physics and for helping advance modern physics research in China.
|
E285685
|
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: Peng Huanwu | Statement: [Peng, hasNotableBearer, Peng Huanwu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peng Huanwu Context triple: [Peng, hasNotableBearer, Peng Huanwu]
-
A.
Zeng Liansong
Zeng Liansong was a Chinese designer best known for creating the national flag of the People's Republic of China.
-
B.
Peng Yuchang
Peng Yuchang is a Chinese actor and singer known for his roles in popular youth films and television dramas.
-
C.
Yin Jichang
Yin Jichang is a Chinese sculptor best known for designing and creating the iconic Five Rams Statue in Guangzhou.
-
D.
Deng Xiansheng
Deng Xiansheng is the birth name of Deng Xiaoping, the paramount Chinese leader who led major economic reforms and opening-up policies in the late 20th century.
-
E.
Mao Yuanxin
Mao Yuanxin is a Chinese political figure known as Mao Zedong’s nephew who briefly held influential positions during the final years of the Cultural Revolution.
- 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: Peng Huanwu Triple: [Peng, hasNotableBearer, Peng Huanwu]
Generated description
Peng Huanwu was a prominent Chinese theoretical physicist known for his contributions to nuclear and particle physics and for helping advance modern physics research in China.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Peng Huanwu Target entity description: Peng Huanwu was a prominent Chinese theoretical physicist known for his contributions to nuclear and particle physics and for helping advance modern physics research in China.
-
A.
Zeng Liansong
Zeng Liansong was a Chinese designer best known for creating the national flag of the People's Republic of China.
-
B.
Peng Yuchang
Peng Yuchang is a Chinese actor and singer known for his roles in popular youth films and television dramas.
-
C.
Yin Jichang
Yin Jichang is a Chinese sculptor best known for designing and creating the iconic Five Rams Statue in Guangzhou.
-
D.
Deng Xiansheng
Deng Xiansheng is the birth name of Deng Xiaoping, the paramount Chinese leader who led major economic reforms and opening-up policies in the late 20th century.
-
E.
Mao Yuanxin
Mao Yuanxin is a Chinese political figure known as Mao Zedong’s nephew who briefly held influential positions during the final years of the Cultural Revolution.
- 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_69a88b0bb30c81908ded03b006d29387 |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abc61a8e248190b5024cca9efd806d |
completed | March 7, 2026, 6:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af98a0ce708190a89b68e8e9053f43 |
completed | March 10, 2026, 4:05 a.m. |
| NEDg | Description generation | batch_69af99416924819099d4acb1a2d60e0c |
completed | March 10, 2026, 4:08 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69af99adadb08190a44f2286b25bf0aa |
completed | March 10, 2026, 4:10 a.m. |
Created at: March 4, 2026, 7:49 p.m.