Triple
T15087733
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zhu Changxun |
E360323
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Changxun
Changxun was the given name of Zhu Changxun, a Ming dynasty imperial prince and son of the Wanli Emperor.
|
E1142659
|
NE FINISHED |
How this triple was built (4 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: Changxun | Statement: [Zhu Changxun, givenName, Changxun]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Changxun Context triple: [Zhu Changxun, givenName, Changxun]
-
A.
Yuncheng
Yuncheng is a major city in southern Shanxi Province, China, known for its historical sites and role as a regional transportation and economic hub.
-
B.
Changshou
Changshou was a Chinese imperial era name used during the reign of Empress Wu Zetian in the Tang dynasty.
-
C.
Xinhui
Xinhui is a district in Jiangmen, Guangdong Province, China, historically known as a significant hometown of overseas Chinese and part of the Pearl River Delta region.
-
D.
Changge City
Changge City is a county-level city in central China's Henan Province, administered by the prefecture-level city of Xuchang and known for its manufacturing and agricultural industries.
-
E.
Xianning
Xianning is a prefecture-level city in southeastern Hubei Province, China, known for its hot springs, karst landscapes, and historical sites.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Changxun Triple: [Zhu Changxun, givenName, Changxun]
Generated description
Changxun was the given name of Zhu Changxun, a Ming dynasty imperial prince and son of the Wanli Emperor.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Changxun Target entity description: Changxun was the given name of Zhu Changxun, a Ming dynasty imperial prince and son of the Wanli Emperor.
-
A.
Yuncheng
Yuncheng is a major city in southern Shanxi Province, China, known for its historical sites and role as a regional transportation and economic hub.
-
B.
Changshou
Changshou was a Chinese imperial era name used during the reign of Empress Wu Zetian in the Tang dynasty.
-
C.
Xinhui
Xinhui is a district in Jiangmen, Guangdong Province, China, historically known as a significant hometown of overseas Chinese and part of the Pearl River Delta region.
-
D.
Changge City
Changge City is a county-level city in central China's Henan Province, administered by the prefecture-level city of Xuchang and known for its manufacturing and agricultural industries.
-
E.
Xianning
Xianning is a prefecture-level city in southeastern Hubei Province, China, known for its hot springs, karst landscapes, and historical sites.
- F. None of above. chosen
Provenance (5 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_69d85a035aa88190b52a139d3a1b7b6d |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e00276d1608190bc310d5b86ecd1d5 |
completed | April 15, 2026, 9:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fed31fa31c8190a22a27f5572e4334 |
completed | May 9, 2026, 6:24 a.m. |
| NEDg | Description generation | batch_69fed3e43328819081017b9666ec324a |
completed | May 9, 2026, 6:27 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fed43b1dd48190b06a7b7fd4d88c93 |
completed | May 9, 2026, 6:29 a.m. |
Created at: April 10, 2026, 3:03 a.m.