Triple
T6913355
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Warlord Era |
E159988
|
entity |
| Predicate | notableFigure |
P4290
|
FINISHED |
| Object | Long Yun |
E444670
|
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: Long Yun | Statement: [Warlord Era, notableFigure, Long Yun]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Long Yun Context triple: [Warlord Era, notableFigure, Long Yun]
-
A.
Long Yun
chosen
Long Yun was a prominent Chinese warlord and politician who governed Yunnan province for much of the Republican era in the early 20th century.
-
B.
Bai Chong Xi
Bai Chongxi was a prominent Chinese Muslim general and political figure of the Nationalist government during the first half of the 20th century.
-
C.
Yang Dezhi
Yang Dezhi was a prominent Chinese general who held senior command roles in the People’s Liberation Army, including leadership during the Sino-Vietnamese War.
-
D.
Yang Hucheng
Yang Hucheng was a Chinese warlord and Nationalist general best known for his role in the Xi'an Incident, which forced Chiang Kai-shek into a united front with the Chinese Communists against Japan.
-
E.
Yin Jichang
Yin Jichang is a Chinese sculptor best known for designing and creating the iconic Five Rams Statue in Guangzhou.
- 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_69c6883ab1008190a07129ff06f625d9 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6d9dbca6c819091d8b65e54ada5d9 |
completed | March 27, 2026, 7:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7584fa7208190a0c5338e20518578 |
completed | March 28, 2026, 4:25 a.m. |
Created at: March 27, 2026, 2:25 p.m.