Triple
T10073371
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beiyang Government |
E213683
|
entity |
| Predicate | headOfState |
P112
|
FINISHED |
| Object | Cao Kun |
E212948
|
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: Cao Kun | Statement: [Beiyang Government, headOfState, Cao Kun]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cao Kun Context triple: [Beiyang Government, headOfState, Cao Kun]
-
A.
Cao Kun
chosen
Cao Kun was a prominent Chinese warlord and politician of the early Republic era who became president of the Beiyang government after consolidating power within the Beiyang Army.
-
B.
Guo Songling
Guo Songling was a Chinese warlord-era general best known for his role in the Fengtian clique and his attempted rebellion against Zhang Zuolin in the 1920s.
-
C.
Li Yuanhong
Li Yuanhong was a Chinese military leader and politician who became a key figure in the 1911 Revolution and later served as president of the Republic of China.
-
D.
Yuan Guiren
Yuan Guiren is a Chinese politician and educator who served as China’s Minister of Education.
-
E.
Chen Yi
Chen Yi was a prominent Chinese Communist military commander and later a senior political leader who served as Foreign Minister of the People’s Republic of 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_69ca839add308190b57d53b4ec21f2d0 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdd015ad488190aee3a2bfb58fb855 |
completed | April 2, 2026, 2:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d98811fd3881909369e0f00f2a8267 |
completed | April 10, 2026, 11:30 p.m. |
Created at: March 30, 2026, 8:59 p.m.