Triple
T15448250
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wu Qingyuan |
E370079
|
entity |
| Predicate | nativeName |
P15
|
FINISHED |
| Object | 呉清源 |
E1157169
|
NE FINISHED |
How this triple was built (2 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: 呉清源 | Statement: [Wu Qingyuan, nativeName, 呉清源]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 呉清源 Context triple: [Wu Qingyuan, nativeName, 呉清源]
-
A.
吴清源
chosen
吴清源（Go Seigen） was a Chinese-born Japanese Go master widely regarded as one of the greatest and most innovative players in the history of the game.
-
B.
Cheng Yanqiu
Cheng Yanqiu was a renowned early 20th-century Peking opera artist celebrated as one of the great "Four Dan" performers for his refined portrayals of female roles and major contributions to the art form’s modern development.
-
C.
蔡鍔
蔡鍔 was a prominent early 20th-century Chinese general and revolutionary best known for leading the opposition to Yuan Shikai’s attempt to restore the monarchy.
-
D.
王貞治
王貞治は、日本プロ野球・読売ジャイアンツで活躍し世界最多本塁打記録を持つ伝説的な打者であり、のちに監督としても成功した人物である。
-
E.
Masataka Kōno (Go player)
Masataka Kōno is a professional Japanese Go player known for his competitive achievements in the modern Go scene.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d85a19180081909925012fbf4e62a3 |
completed | April 10, 2026, 2:02 a.m. |
| NER | Named-entity recognition | batch_69e03ef9334c81908541e231b43eb012 |
completed | April 16, 2026, 1:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff2cf9eae881909b5dc74c55a04ff0 |
completed | May 9, 2026, 12:47 p.m. |
Created at: April 10, 2026, 3:21 a.m.