Triple
T15286541
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Xuande Emperor |
E365414
|
entity |
| Predicate | courtesyName |
P570
|
FINISHED |
| Object | Dezhi |
E365414
|
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: Dezhi | Statement: [Xuande Emperor, courtesyName, Dezhi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dezhi Context triple: [Xuande Emperor, courtesyName, Dezhi]
-
A.
Dezhi
chosen
Dezhi is the courtesy name of the Xuande Emperor, a Ming dynasty ruler of China known for his relatively stable and prosperous reign in the early 15th century.
-
B.
Deyu
Deyu is the courtesy name of the Hongguang Emperor, a short-lived Southern Ming ruler who attempted to restore the Ming dynasty after the fall of Beijing to the Qing.
-
C.
Dezong
Dezong is the posthumous temple name of the Guangxu Emperor, a late Qing dynasty ruler of China.
-
D.
Dongsheng
Dongsheng is a Chinese given name commonly used for males.
-
E.
Dunhua
Dunhua is a county-level city in northeastern China's Jilin Province, known for its location within the Yanbian Korean Autonomous Prefecture and its mix of Han and Korean cultural influences.
- 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_69d85a103d9081908c1ea6c4c73ac8e3 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e00e551bb0819094db097285443740 |
completed | April 15, 2026, 10:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feef798a588190981c77e6f4c6be78 |
completed | May 9, 2026, 8:25 a.m. |
Created at: April 10, 2026, 3:15 a.m.