Triple
T8210798
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ren Zhengfei |
E191810
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Meng Jun
Meng Jun is a Chinese businesswoman best known as the former wife of Huawei founder Ren Zhengfei and the mother of the company’s CFO, Meng Wanzhou.
|
E738225
|
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 Jun | Statement: [Ren Zhengfei, spouse, Meng Jun]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Meng Jun Context triple: [Ren Zhengfei, spouse, Meng Jun]
-
A.
Zhu Junyi
Zhu Junyi is a former senior Chinese police and security official best known for his involvement in major corruption scandals.
-
B.
Jiang Wenli
Jiang Wenli is a renowned Chinese actress celebrated for her versatile performances in film and television dramas.
-
C.
Jun Xia
Jun Xia is a Chinese architect best known for serving as the lead designer of Shanghai Tower, one of the world’s tallest skyscrapers.
-
D.
Lu Jun
Lu Jun is a family member of Lu Lingzi, the Chinese graduate student who was killed in the 2013 Boston Marathon bombing.
-
E.
He Mengxiong
He Mengxiong was a Chinese military officer and revolutionary associated with early 20th-century nationalist movements.
- 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 Jun Triple: [Ren Zhengfei, spouse, Meng Jun]
Generated description
Meng Jun is a Chinese businesswoman best known as the former wife of Huawei founder Ren Zhengfei and the mother of the company’s CFO, Meng Wanzhou.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Meng Jun Target entity description: Meng Jun is a Chinese businesswoman best known as the former wife of Huawei founder Ren Zhengfei and the mother of the company’s CFO, Meng Wanzhou.
-
A.
Zhu Junyi
Zhu Junyi is a former senior Chinese police and security official best known for his involvement in major corruption scandals.
-
B.
Jiang Wenli
Jiang Wenli is a renowned Chinese actress celebrated for her versatile performances in film and television dramas.
-
C.
Jun Xia
Jun Xia is a Chinese architect best known for serving as the lead designer of Shanghai Tower, one of the world’s tallest skyscrapers.
-
D.
Lu Jun
Lu Jun is a family member of Lu Lingzi, the Chinese graduate student who was killed in the 2013 Boston Marathon bombing.
-
E.
He Mengxiong
He Mengxiong was a Chinese military officer and revolutionary associated with early 20th-century nationalist movements.
- 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_69ca82c8c054819087fedd9a5436b8a3 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb76dd881c8190adcbeb2f33d3295c |
completed | March 31, 2026, 7:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce4d731b248190a440e1289e655b74 |
completed | April 2, 2026, 11:05 a.m. |
| NEDg | Description generation | batch_69ce4f556a408190b404481a32b2457b |
completed | April 2, 2026, 11:13 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ce503737a4819083ebf9f410eac826 |
completed | April 2, 2026, 11:17 a.m. |
Created at: March 30, 2026, 5:44 p.m.