Triple
T7947600
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liu Bei |
E184534
|
entity |
| Predicate | eraName |
P2938
|
FINISHED |
| Object | Zhangwu |
E695251
|
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: Zhangwu | Statement: [Liu Bei, eraName, Zhangwu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zhangwu Context triple: [Liu Bei, eraName, Zhangwu]
-
A.
Zhangwu
chosen
Zhangwu was a historical Chinese era name used during the Three Kingdoms period, specifically associated with the Shu Han state.
-
B.
Luzhi
Luzhi is an ancient canal town near Suzhou in China, renowned for its well-preserved waterways, stone bridges, and traditional Jiangnan architecture.
-
C.
Ruchang
Ruchang is a Chinese given name most notably borne by Ding Ruchang, a late Qing dynasty naval commander.
-
D.
Zhizhong
Zhizhong is a Chinese given name shared by various individuals, including historical and contemporary figures.
-
E.
Wuyuan
Wuyuan is a historic county in northeastern Jiangxi, China, famed for its well-preserved Huizhou-style architecture and picturesque rural landscapes.
- 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_69ca8291c2008190b1b8832c87814bcf |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3b2abdbc819085ae53826d36af3b |
completed | March 31, 2026, 3:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc63ad5fbc819082f7900cd618bd0e |
completed | April 1, 2026, 12:15 a.m. |
Created at: March 30, 2026, 5:09 p.m.