Triple
T3955289
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wu dialects |
E84960
|
entity |
| Predicate | hasSubgroup |
P747
|
FINISHED |
| Object |
Taizhou Wu
Taizhou Wu is a regional variety of the Wu group of Chinese dialects spoken primarily in and around Taizhou in Zhejiang province.
|
E402909
|
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: Taizhou Wu | Statement: [Wu dialects, hasSubgroup, Taizhou Wu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Taizhou Wu Context triple: [Wu dialects, hasSubgroup, Taizhou Wu]
-
A.
Wu Qingyuan
Wu Qingyuan, better known internationally as Go Seigen, was a Chinese-born Japanese Go master widely regarded as one of the greatest and most innovative players in the history of the game.
-
B.
Ye Zhengxian
Ye Zhengxian is known primarily as a child of the prominent Chinese military leader Ye Ting.
-
C.
Zhang Wenqi
Zhang Wenqi is a Chinese basketball player best known for having played professionally for the Shanghai Sharks in the Chinese Basketball Association.
-
D.
Wu Jingyu
Wu Jingyu is a Chinese taekwondo athlete and multiple-time Olympic gold medalist renowned as one of the sport’s most successful competitors.
-
E.
Wu Yi
Wu Yi is a Chinese politician who served as Vice Premier of the State Council and was widely known for her leadership in economic policy and public health crises such as the SARS outbreak.
- 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: Taizhou Wu Triple: [Wu dialects, hasSubgroup, Taizhou Wu]
Generated description
Taizhou Wu is a regional variety of the Wu group of Chinese dialects spoken primarily in and around Taizhou in Zhejiang province.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Taizhou Wu Target entity description: Taizhou Wu is a regional variety of the Wu group of Chinese dialects spoken primarily in and around Taizhou in Zhejiang province.
-
A.
Wu Qingyuan
Wu Qingyuan, better known internationally as Go Seigen, was a Chinese-born Japanese Go master widely regarded as one of the greatest and most innovative players in the history of the game.
-
B.
Ye Zhengxian
Ye Zhengxian is known primarily as a child of the prominent Chinese military leader Ye Ting.
-
C.
Zhang Wenqi
Zhang Wenqi is a Chinese basketball player best known for having played professionally for the Shanghai Sharks in the Chinese Basketball Association.
-
D.
Wu Jingyu
Wu Jingyu is a Chinese taekwondo athlete and multiple-time Olympic gold medalist renowned as one of the sport’s most successful competitors.
-
E.
Wu Yi
Wu Yi is a Chinese politician who served as Vice Premier of the State Council and was widely known for her leadership in economic policy and public health crises such as the SARS outbreak.
- 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_69aed934fbfc8190847068e4546de963 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef93d742c81908639c843193d78fd |
completed | March 9, 2026, 4:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b533aea08c8190b83d83e3ba89848c |
completed | March 14, 2026, 10:08 a.m. |
| NEDg | Description generation | batch_69b537f7e2e481909b7a337c130bca7a |
completed | March 14, 2026, 10:27 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b538a7f8e4819087a74e96255e7c45 |
completed | March 14, 2026, 10:30 a.m. |
Created at: March 9, 2026, 3:30 p.m.