Triple
T21171299
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wang Yangming |
E521696
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Yangming |
—
|
NE NERFINISHED |
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: Yangming | Statement: [Wang Yangming, givenName, Yangming]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yangming Context triple: [Wang Yangming, givenName, Yangming]
-
A.
Yangming
chosen
Yangming is the art name of Wang Yangming, a prominent Ming dynasty Neo-Confucian philosopher, statesman, and military leader known for his influential doctrine of the unity of knowledge and action.
-
B.
Chuanzhi
Chuanzhi is the given name of Liu Chuanzhi, the Chinese entrepreneur best known as the founder of Lenovo.
-
C.
Mingzhe
Mingzhe is a given name associated with Peter Ma Mingzhe, a notable Chinese business figure and entrepreneur.
-
D.
Fu Sheng
Fu Sheng was a short-lived and notoriously cruel emperor of the Former Qin state during China’s Sixteen Kingdoms period.
-
E.
Shen Dao
Shen Dao is the ceremonial spirit road leading to the Ming Tombs near Beijing, lined with stone statues and monuments that honor deceased emperors.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b50e30748190b186824a206d39b9 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7271351f08190b609a6c280c9a02a |
completed | April 21, 2026, 7:28 a.m. |
Created at: April 16, 2026, 3 p.m.