Triple
T2122096
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Western China |
E43946
|
entity |
| Predicate | hasEthnicGroup |
P1898
|
FINISHED |
| Object | Hui |
E132243
|
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: Hui | Statement: [Western China, hasEthnicGroup, Hui]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hui Context triple: [Western China, hasEthnicGroup, Hui]
-
A.
Hui
chosen
The Hui are a predominantly Muslim ethnic group in China known for their integration of Islamic faith with Han Chinese language and cultural practices.
-
B.
Kaihui
Kaihui is a Chinese given name most notably borne by Yang Kaihui, the revolutionary and early partner of Mao Zedong.
-
C.
Luoyi
Luoyi was an ancient Chinese city that served as a major political and cultural center of the Zhou dynasty.
-
D.
Xuan
Xuan is a Vietnamese surname commonly used as a family name in Vietnam.
-
E.
Zhizhong
Zhizhong is a Chinese given name shared by various individuals, including historical and contemporary figures.
- 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_69a88717cfe48190b7ecdd68c824848a |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abbb51e8088190a1aeafee4e8dff63 |
completed | March 7, 2026, 5:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae58cd22c8819096dfd06d16703bf8 |
completed | March 9, 2026, 5:21 a.m. |
Created at: March 4, 2026, 7:44 p.m.