Triple
T16731481
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Siku Quanshu |
E406601
|
entity |
| Predicate | copyLocation |
P124420
|
FINISHED |
| Object |
Wenhui Ge, Yangzhou
Wenhui Ge in Yangzhou is a historic pavilion and cultural site known for housing important classical Chinese texts and serving as a center of traditional scholarship.
|
E1230229
|
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: Wenhui Ge, Yangzhou | Statement: [Siku Quanshu, copyLocation, Wenhui Ge, Yangzhou]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wenhui Ge, Yangzhou Context triple: [Siku Quanshu, copyLocation, Wenhui Ge, Yangzhou]
-
A.
Gao-Yang Yue
Gao-Yang Yue is a regional variety of Yue Chinese spoken primarily in parts of Guangdong province in southern China.
-
B.
Taizhou Wu
Taizhou Wu is a regional variety of the Wu group of Chinese dialects spoken primarily in and around Taizhou in Zhejiang province.
-
C.
Huangwei Yu
Huangwei Yu is a small outlying islet associated with the Diaoyutai (Senkaku) Islands in the East China Sea, known primarily within the context of regional territorial disputes.
-
D.
Huangwei Yu
Huangwei Yu is the Chinese name of the character Kubashima.
-
E.
Yuhuai Wu
Yuhuai Wu is an AI researcher and entrepreneur known for his work on large language models and as a member of Elon Musk’s xAI team.
- 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: Wenhui Ge, Yangzhou Triple: [Siku Quanshu, copyLocation, Wenhui Ge, Yangzhou]
Generated description
Wenhui Ge in Yangzhou is a historic pavilion and cultural site known for housing important classical Chinese texts and serving as a center of traditional scholarship.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Wenhui Ge, Yangzhou Target entity description: Wenhui Ge in Yangzhou is a historic pavilion and cultural site known for housing important classical Chinese texts and serving as a center of traditional scholarship.
-
A.
Gao-Yang Yue
Gao-Yang Yue is a regional variety of Yue Chinese spoken primarily in parts of Guangdong province in southern China.
-
B.
Taizhou Wu
Taizhou Wu is a regional variety of the Wu group of Chinese dialects spoken primarily in and around Taizhou in Zhejiang province.
-
C.
Huangwei Yu
Huangwei Yu is a small outlying islet associated with the Diaoyutai (Senkaku) Islands in the East China Sea, known primarily within the context of regional territorial disputes.
-
D.
Huangwei Yu
Huangwei Yu is the Chinese name of the character Kubashima.
-
E.
Yuhuai Wu
Yuhuai Wu is an AI researcher and entrepreneur known for his work on large language models and as a member of Elon Musk’s xAI team.
- 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_69d8838f242881908abd8bc138795886 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e39c362bb88190921fab43d76c3ee8 |
completed | April 18, 2026, 2:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a009d4a94688190aabe56c34e8cc2c3 |
completed | May 10, 2026, 2:59 p.m. |
| NEDg | Description generation | batch_6a009dd925308190a82c6ef014b37333 |
completed | May 10, 2026, 3:01 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a009e9b9874819084060408cdc44d0b |
completed | May 10, 2026, 3:04 p.m. |
Created at: April 10, 2026, 5:20 a.m.