Triple
T7946033
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miao languages |
E184499
|
entity |
| Predicate | hasMemberLanguage |
P7390
|
FINISHED |
| Object |
Qo Xiong
Qo Xiong is a variety of the Miao (Hmong-Mien) language family spoken by Miao communities in parts of China.
|
E731627
|
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: Qo Xiong | Statement: [Miao languages, hasMemberLanguage, Qo Xiong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Qo Xiong Context triple: [Miao languages, hasMemberLanguage, Qo Xiong]
-
A.
Hui Xiong
Hui Xiong is a prominent computer scientist and data mining researcher recognized for his influential contributions to knowledge discovery and data analytics.
-
B.
Xiong Yi
Xiong Yi was the legendary early ruler credited with establishing the ancient Chinese state of Chu during the Zhou dynasty.
-
C.
Dou Xian
Dou Xian was a powerful Eastern Han dynasty general and statesman best known for leading decisive campaigns that broke the power of the Northern Xiongnu.
-
D.
Cui Hao
Cui Hao was a prominent poet of the Tang dynasty in China, best known for his evocative landscape and frontier poems.
-
E.
He Xuntian
He Xuntian is a contemporary Chinese composer known for his innovative fusion of traditional Chinese musical elements with modern compositional techniques.
- 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: Qo Xiong Triple: [Miao languages, hasMemberLanguage, Qo Xiong]
Generated description
Qo Xiong is a variety of the Miao (Hmong-Mien) language family spoken by Miao communities in parts of China.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Qo Xiong Target entity description: Qo Xiong is a variety of the Miao (Hmong-Mien) language family spoken by Miao communities in parts of China.
-
A.
Hui Xiong
Hui Xiong is a prominent computer scientist and data mining researcher recognized for his influential contributions to knowledge discovery and data analytics.
-
B.
Xiong Yi
Xiong Yi was the legendary early ruler credited with establishing the ancient Chinese state of Chu during the Zhou dynasty.
-
C.
Dou Xian
Dou Xian was a powerful Eastern Han dynasty general and statesman best known for leading decisive campaigns that broke the power of the Northern Xiongnu.
-
D.
Cui Hao
Cui Hao was a prominent poet of the Tang dynasty in China, best known for his evocative landscape and frontier poems.
-
E.
He Xuntian
He Xuntian is a contemporary Chinese composer known for his innovative fusion of traditional Chinese musical elements with modern compositional techniques.
- 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_69cb3b29a570819091a2ac185a8d57c4 |
completed | March 31, 2026, 3:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce01c37978819090922f7fc273edc9 |
completed | April 2, 2026, 5:42 a.m. |
| NEDg | Description generation | batch_69ce064211e48190b558d4355be659ba |
completed | April 2, 2026, 6:01 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ce07a390048190ac26a7e3d3d561e0 |
completed | April 2, 2026, 6:07 a.m. |
Created at: March 30, 2026, 5:09 p.m.