Triple
T5884232
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yue Chinese |
E130821
|
entity |
| Predicate | hasVariety |
P455
|
FINISHED |
| Object |
Siyi Yue
Siyi Yue is a regional variety of Yue Chinese spoken primarily in the Siyi (Four Counties) area of Guangdong, China.
|
E554518
|
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: Siyi Yue | Statement: [Yue Chinese, hasVariety, Siyi Yue]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Siyi Yue Context triple: [Yue Chinese, hasVariety, Siyi Yue]
-
A.
Yue
Yue is a given name that appears in various East Asian cultures, often associated with meanings like "moon" or "delight" depending on the characters used.
-
B.
Qiying
Qiying was a Qing dynasty statesman and diplomat who played a key role in negotiating several unequal treaties with Western powers in the mid-19th century.
-
C.
Shaoqi
Shaoqi is the given name of Liu Shaoqi, a prominent Chinese revolutionary leader and former President of the People’s Republic of China.
-
D.
Yunwen
Yunwen was the personal name of the Jianwen Emperor, a Ming dynasty ruler of China known for his short and turbulent reign and subsequent mysterious disappearance.
-
E.
Zhenyuan
Zhenyuan was a late 19th-century Chinese ironclad battleship of the Beiyang Fleet that played a prominent role in the First Sino-Japanese War.
- 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: Siyi Yue Triple: [Yue Chinese, hasVariety, Siyi Yue]
Generated description
Siyi Yue is a regional variety of Yue Chinese spoken primarily in the Siyi (Four Counties) area of Guangdong, China.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Siyi Yue Target entity description: Siyi Yue is a regional variety of Yue Chinese spoken primarily in the Siyi (Four Counties) area of Guangdong, China.
-
A.
Yue
Yue is a given name that appears in various East Asian cultures, often associated with meanings like "moon" or "delight" depending on the characters used.
-
B.
Qiying
Qiying was a Qing dynasty statesman and diplomat who played a key role in negotiating several unequal treaties with Western powers in the mid-19th century.
-
C.
Shaoqi
Shaoqi is the given name of Liu Shaoqi, a prominent Chinese revolutionary leader and former President of the People’s Republic of China.
-
D.
Yunwen
Yunwen was the personal name of the Jianwen Emperor, a Ming dynasty ruler of China known for his short and turbulent reign and subsequent mysterious disappearance.
-
E.
Zhenyuan
Zhenyuan was a late 19th-century Chinese ironclad battleship of the Beiyang Fleet that played a prominent role in the First Sino-Japanese War.
- 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_69c0085628dc8190b334c1b44c067efc |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0367743508190bae211e9ce8f9690 |
completed | March 22, 2026, 6:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0b13839f48190b23f22d5317eb571 |
completed | March 23, 2026, 3:19 a.m. |
| NEDg | Description generation | batch_69c0b27438a08190ab6b72c8fd682bf6 |
completed | March 23, 2026, 3:24 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c0b309a70081908ad3e819879b17e4 |
completed | March 23, 2026, 3:27 a.m. |
Created at: March 22, 2026, 3:57 p.m.