Triple
T19324612
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wanrong |
E483315
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Wanrong |
—
|
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: Wanrong | Statement: [Wanrong, givenName, Wanrong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wanrong Context triple: [Wanrong, givenName, Wanrong]
-
A.
Wanrong
chosen
Wanrong was the last empress of China as the consort of Puyi, the final emperor of the Qing dynasty.
-
B.
Yongrong
Yongrong was a Qing dynasty imperial prince, known as one of the sons of the Qianlong Emperor and a member of the high Manchu nobility.
-
C.
Yanxi
Yanxi was a regnal era of the Shu Han state during China’s Three Kingdoms period.
-
D.
Weiwuying
Weiwuying is a major performing arts center in Kaohsiung, Taiwan, renowned for its striking contemporary architecture and large-scale cultural facilities.
-
E.
Wanyan Xiyin
Wanyan Xiyin was a prominent Jurchen statesman and scholar of the Jin dynasty best known for devising the Jurchen script used to write the Jurchen language.
- 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_69d8e8d13e3c81909d91d1d5ec37c095 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e60d8af43c81908e5a8780c35a8e1d |
completed | April 20, 2026, 11:27 a.m. |
Created at: April 10, 2026, 1:32 p.m.