Triple
T1524814
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tan Dun |
E32311
|
entity |
| Predicate | nativeName |
P15
|
FINISHED |
| Object | 谭盾 |
E32311
|
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: 谭盾 | Statement: [Tan Dun, nativeName, 谭盾]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 谭盾 Context triple: [Tan Dun, nativeName, 谭盾]
-
A.
Tan Dun
chosen
Tan Dun is a Chinese contemporary composer and conductor renowned for blending traditional Chinese music with Western classical forms, including his Oscar-winning score for "Crouching Tiger, Hidden Dragon."
-
B.
高錕
高錕是一位华裔物理学家和电机工程师，被誉为“光纤之父”，因在光纤通信领域的开创性贡献而获得诺贝尔物理学奖。
-
C.
Wang Shu
Wang Shu is a renowned Chinese architect celebrated for blending traditional craftsmanship with contemporary design, earning him international acclaim.
-
D.
Song Shilun
Song Shilun was a prominent Chinese general of the People’s Volunteer Army during the Korean War, noted for leading Chinese forces in major campaigns against United Nations troops.
-
E.
Liang Xiaosheng
Liang Xiaosheng is a prominent Chinese writer and scholar best known for his realist novels depicting ordinary people's lives in contemporary China.
- 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_69a885e9b0ac819093a9806ad0efc82c |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a9080175588190bb3b1d4b17966f2f |
completed | March 5, 2026, 4:35 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad2951c1ec8190b7ac04cd820a2bfa |
completed | March 8, 2026, 7:46 a.m. |
Created at: March 4, 2026, 7:26 p.m.