Triple
T11831732
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dorgon |
E281407
|
entity |
| Predicate | sibling |
P363
|
FINISHED |
| Object | Hong Taiji |
E190908
|
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: Hong Taiji | Statement: [Dorgon, sibling, Hong Taiji]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hong Taiji Context triple: [Dorgon, sibling, Hong Taiji]
-
A.
Hong Taiji
chosen
Hong Taiji was a 17th-century Manchu ruler who transformed the Later Jin into the Qing dynasty and laid the foundations for Qing rule over China.
-
B.
Shunzhi Emperor
The Shunzhi Emperor was the early Qing dynasty ruler who oversaw the consolidation of Manchu control over China following the fall of the Ming dynasty.
-
C.
Dorgon
Dorgon was a powerful Manchu prince and regent of the early Qing dynasty who led the conquest of Ming China and helped establish Qing rule over the empire.
-
D.
Nurhaci
Nurhaci was the Jurchen chieftain who unified the Manchu tribes and laid the foundations for the Qing dynasty’s conquest of China.
-
E.
Kangxi
Kangxi was a long-reigning and influential emperor of the Qing dynasty who consolidated imperial power, expanded the empire, and presided over a period of stability and cultural flourishing in 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_69d6ab276f8c8190b1966a0ef11349ac |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a62c95988190a45dbaa7001c8846 |
completed | April 10, 2026, 7:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f16741d9a08190b6d6d5e59dfa41b8 |
completed | April 29, 2026, 2:04 a.m. |
Created at: April 8, 2026, 9:43 p.m.