Triple
T17180044
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wang Da-hong |
E416957
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Da-hong
Da-hong is the given name of Wang Da-hong, a prominent Taiwanese architect known for blending modernist design with traditional Chinese elements.
|
E1254667
|
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: Da-hong | Statement: [Wang Da-hong, givenName, Da-hong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Da-hong Context triple: [Wang Da-hong, givenName, Da-hong]
-
A.
Yuanhong
Yuanhong is a Chinese given name that appears in the full name of the historical figure Li Yuanhong.
-
B.
Minhong
Minhong is the given Chinese name of Michael Yu, the founder of New Oriental Education & Technology Group.
-
C.
Yangsheng
Yangsheng is a traditional Chinese practice focused on nurturing life and cultivating health and longevity through balanced living, diet, exercise, and spiritual refinement.
-
D.
Duanhua
Duanhua was a Qing dynasty Manchu prince and high-ranking regent who was overthrown and later executed following the Xinyou Coup of 1861.
-
E.
Dayong
Dayong is the former name of the city now known as Zhangjiajie in Hunan Province, China, famed for its dramatic sandstone pillar landscapes.
- 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: Da-hong Triple: [Wang Da-hong, givenName, Da-hong]
Generated description
Da-hong is the given name of Wang Da-hong, a prominent Taiwanese architect known for blending modernist design with traditional Chinese elements.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Da-hong Target entity description: Da-hong is the given name of Wang Da-hong, a prominent Taiwanese architect known for blending modernist design with traditional Chinese elements.
-
A.
Yuanhong
Yuanhong is a Chinese given name that appears in the full name of the historical figure Li Yuanhong.
-
B.
Minhong
Minhong is the given Chinese name of Michael Yu, the founder of New Oriental Education & Technology Group.
-
C.
Yangsheng
Yangsheng is a traditional Chinese practice focused on nurturing life and cultivating health and longevity through balanced living, diet, exercise, and spiritual refinement.
-
D.
Duanhua
Duanhua was a Qing dynasty Manchu prince and high-ranking regent who was overthrown and later executed following the Xinyou Coup of 1861.
-
E.
Dayong
Dayong is the former name of the city now known as Zhangjiajie in Hunan Province, China, famed for its dramatic sandstone pillar landscapes.
- 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_69d886d5f34c8190b24564dfaa63f3fb |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3fc10afb48190a71f4a46f0280a14 |
completed | April 18, 2026, 9:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a014847a19481909b1249c2fe428bfc |
completed | May 11, 2026, 3:08 a.m. |
| NEDg | Description generation | batch_6a014cf269b48190bf58eb71a9fec897 |
completed | May 11, 2026, 3:28 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a014d5d10b4819086969145c2d4fb56 |
completed | May 11, 2026, 3:30 a.m. |
Created at: April 10, 2026, 5:37 a.m.