Triple
T8482233
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fan Hui |
E200547
|
entity |
| Predicate | nativeName |
P15
|
FINISHED |
| Object |
樊麾
樊麾 is a Chinese-born French professional Go player best known for being the first human defeated by DeepMind’s AlphaGo program.
|
E736775
|
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: 樊麾 | Statement: [Fan Hui, nativeName, 樊麾]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 樊麾 Context triple: [Fan Hui, nativeName, 樊麾]
-
A.
Fan Ji
Fan Ji was a consort of King Zhuang of Chu, a prominent ruler of the Spring and Autumn period in ancient China.
-
B.
Fan Wei
Fan Wei is a mathematician known for his research in combinatorics and related areas, and for being a doctoral student of Fan Chung.
-
C.
Fan Wei
Fan Wei is a Chinese entrepreneur best known as a co-founder of the multinational conglomerate Fosun International.
-
D.
Huang Zhiyong
Huang Zhiyong was a Chinese military officer and notable graduate of the Yunnan Military Academy who participated in early 20th-century military and political affairs in China.
-
E.
Fu Cong
Fu Cong is a Chinese diplomat who serves as the Permanent Representative of the People’s Republic of China to the United Nations.
- 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: 樊麾 Triple: [Fan Hui, nativeName, 樊麾]
Generated description
樊麾 is a Chinese-born French professional Go player best known for being the first human defeated by DeepMind’s AlphaGo program.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: 樊麾 Target entity description: 樊麾 is a Chinese-born French professional Go player best known for being the first human defeated by DeepMind’s AlphaGo program.
-
A.
Fan Ji
Fan Ji was a consort of King Zhuang of Chu, a prominent ruler of the Spring and Autumn period in ancient China.
-
B.
Fan Wei
Fan Wei is a mathematician known for his research in combinatorics and related areas, and for being a doctoral student of Fan Chung.
-
C.
Fan Wei
Fan Wei is a Chinese entrepreneur best known as a co-founder of the multinational conglomerate Fosun International.
-
D.
Huang Zhiyong
Huang Zhiyong was a Chinese military officer and notable graduate of the Yunnan Military Academy who participated in early 20th-century military and political affairs in China.
-
E.
Fu Cong
Fu Cong is a Chinese diplomat who serves as the Permanent Representative of the People’s Republic of China to the United Nations.
- 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_69ca831b17988190a1f3f3413d57b820 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe53638c48190b742fc51d1b4442a |
completed | March 31, 2026, 3:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce3a2b2e9081909f19712946c6ec20 |
completed | April 2, 2026, 9:43 a.m. |
| NEDg | Description generation | batch_69ce3b4008a0819096bb44b46f510213 |
completed | April 2, 2026, 9:47 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ce3c000e608190adf1b6499d382529 |
completed | April 2, 2026, 9:50 a.m. |
Created at: March 30, 2026, 6:12 p.m.