Triple
T7700899
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Xue |
E174489
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Xue Susu
Xue Susu was a renowned late-Ming dynasty courtesan, painter, and poet celebrated for her artistic talent, beauty, and unconventional, independent lifestyle.
|
E685137
|
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: Xue Susu | Statement: [Xue, hasNotableBearer, Xue Susu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Xue Susu Context triple: [Xue, hasNotableBearer, Xue Susu]
-
A.
Ling Xiaosu
Ling Xiaosu is a Chinese actor known for his roles in television dramas and for his former marriage to actress Yao Chen.
-
B.
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.
-
C.
Duan Xiushi
Duan Xiushi was a Tang dynasty military general best known for his role in the mid-8th century conflicts between the Tang Empire and the Abbasid Caliphate in Central Asia.
-
D.
Li Jingxi
Li Jingxi was a Chinese politician and statesman who briefly served as premier during the early years of the Republic of China.
-
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: Xue Susu Triple: [Xue, hasNotableBearer, Xue Susu]
Generated description
Xue Susu was a renowned late-Ming dynasty courtesan, painter, and poet celebrated for her artistic talent, beauty, and unconventional, independent lifestyle.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Xue Susu Target entity description: Xue Susu was a renowned late-Ming dynasty courtesan, painter, and poet celebrated for her artistic talent, beauty, and unconventional, independent lifestyle.
-
A.
Ling Xiaosu
Ling Xiaosu is a Chinese actor known for his roles in television dramas and for his former marriage to actress Yao Chen.
-
B.
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.
-
C.
Duan Xiushi
Duan Xiushi was a Tang dynasty military general best known for his role in the mid-8th century conflicts between the Tang Empire and the Abbasid Caliphate in Central Asia.
-
D.
Li Jingxi
Li Jingxi was a Chinese politician and statesman who briefly served as premier during the early years of the Republic of China.
-
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_69c6995a72cc8190998e56daa6f8e453 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c70288d02c819093d6f0e47707d0a3 |
completed | March 27, 2026, 10:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8b502ebc0819095b0dc7096c2b997 |
completed | March 29, 2026, 5:13 a.m. |
| NEDg | Description generation | batch_69c8b5a1f758819086f4f4a2b6221369 |
completed | March 29, 2026, 5:16 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c8b649e91c8190b18f8caacb584327 |
completed | March 29, 2026, 5:19 a.m. |
Created at: March 27, 2026, 4:03 p.m.