Triple
T3641503
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wanli Emperor |
E77196
|
entity |
| Predicate | child |
P120
|
FINISHED |
| Object | Zhu Changxun |
E360323
|
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: Zhu Changxun | Statement: [Wanli Emperor, child, Zhu Changxun]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zhu Changxun Context triple: [Wanli Emperor, child, Zhu Changxun]
-
A.
Zhu Changxun
chosen
Zhu Changxun was a Ming dynasty prince and the father of the Hongguang Emperor, whose death at the hands of rebel forces became a notable episode in the dynasty’s final years.
-
B.
Peng Yuchang
Peng Yuchang is a Chinese actor and singer known for his roles in popular youth films and television dramas.
-
C.
Zhu Jianshen
Zhu Jianshen, better known as the Chenghua Emperor, was a Ming dynasty ruler whose long reign saw both cultural flourishing and increasing court corruption in 15th-century China.
-
D.
Zhu Zhanyong
Zhu Zhanyong was a Ming dynasty imperial prince, known primarily as a son of the Hongxi Emperor of China.
-
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_69ad85de1b988190a45f8dbfebc806fc |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc359a91481908aef1c022f45e55c |
completed | March 8, 2026, 6:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5d03dbd348190aaaa58a352982248 |
completed | March 14, 2026, 9:16 p.m. |
Created at: March 8, 2026, 3:24 p.m.