Triple
T8577036
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ke Jie |
E203072
|
entity |
| Predicate | nativeName |
P15
|
FINISHED |
| Object | 柯洁 |
E203072
|
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: 柯洁 | Statement: [Ke Jie, nativeName, 柯洁]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 柯洁 Context triple: [Ke Jie, nativeName, 柯洁]
-
A.
Ke Jie
chosen
Ke Jie is a Chinese professional Go player widely regarded as one of the strongest players of his generation.
-
B.
Lee Sedol
Lee Sedol is a South Korean professional Go player renowned as one of the strongest players in history and for his landmark 2016 match against DeepMind's AlphaGo.
-
C.
Wu Lei
Wu Lei is a prominent Chinese actor and former child star known for his roles in popular television dramas and films.
-
D.
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.
-
E.
Zou Jingzhi
Zou Jingzhi is a Chinese screenwriter and playwright known for his work on acclaimed films and television dramas, including collaborations with director Zhang Yimou.
- 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_69ca8328ebe481909a8c038fa79959b4 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbea97787481909ebbaa45f59cbdaa |
completed | March 31, 2026, 3:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce899dd7d48190b44338b92ad68bd0 |
completed | April 2, 2026, 3:22 p.m. |
Created at: March 30, 2026, 6:22 p.m.