Triple
T7947803
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | High Tang |
E184538
|
entity |
| Predicate | hasNotablePoet |
P4290
|
FINISHED |
| Object |
Meng Haoran
Meng Haoran was a renowned High Tang poet celebrated for his tranquil landscape and nature-themed verse that deeply influenced classical Chinese poetry.
|
E712114
|
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: Meng Haoran | Statement: [High Tang, hasNotablePoet, Meng Haoran]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Meng Haoran Context triple: [High Tang, hasNotablePoet, Meng Haoran]
-
A.
Qi Xin
Qi Xin is a Chinese revolutionary and former Party official best known as the mother of China’s paramount leader Xi Jinping.
-
B.
Yan Xiu
Yan Xiu was a prominent early 20th-century Chinese educator and reformer who played a key role in modernizing China's education system.
-
C.
Li Bai
Li Bai was a renowned Chinese poet of the Tang dynasty, celebrated for his romantic, imaginative verse and mastery of classical Chinese poetry.
-
D.
Tao Qian
Tao Qian was a late Eastern Han dynasty warlord and governor of Xu Province, best known for ceding his territory to Liu Bei before his death.
-
E.
Wang Wei
Wang Wei was a renowned Tang dynasty Chinese poet, painter, and musician celebrated for his landscape poetry and contributions to Chan (Zen) Buddhist aesthetics.
- 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: Meng Haoran Triple: [High Tang, hasNotablePoet, Meng Haoran]
Generated description
Meng Haoran was a renowned High Tang poet celebrated for his tranquil landscape and nature-themed verse that deeply influenced classical Chinese poetry.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Meng Haoran Target entity description: Meng Haoran was a renowned High Tang poet celebrated for his tranquil landscape and nature-themed verse that deeply influenced classical Chinese poetry.
-
A.
Qi Xin
Qi Xin is a Chinese revolutionary and former Party official best known as the mother of China’s paramount leader Xi Jinping.
-
B.
Yan Xiu
Yan Xiu was a prominent early 20th-century Chinese educator and reformer who played a key role in modernizing China's education system.
-
C.
Li Bai
Li Bai was a renowned Chinese poet of the Tang dynasty, celebrated for his romantic, imaginative verse and mastery of classical Chinese poetry.
-
D.
Tao Qian
Tao Qian was a late Eastern Han dynasty warlord and governor of Xu Province, best known for ceding his territory to Liu Bei before his death.
-
E.
Wang Wei
Wang Wei was a renowned Tang dynasty Chinese poet, painter, and musician celebrated for his landscape poetry and contributions to Chan (Zen) Buddhist aesthetics.
- 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_69ca8291c2008190b1b8832c87814bcf |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3b2abdbc819085ae53826d36af3b |
completed | March 31, 2026, 3:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc937366b8819091f08f8f7facf6f6 |
completed | April 1, 2026, 3:39 a.m. |
| NEDg | Description generation | batch_69cc955542fc8190a84be60f4efea915 |
completed | April 1, 2026, 3:47 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cc964c6b308190ae121072b1180268 |
completed | April 1, 2026, 3:51 a.m. |
Created at: March 30, 2026, 5:10 p.m.