Triple
T15361348
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kaiming He |
E367295
|
entity |
| Predicate | coAuthor |
P398
|
FINISHED |
| Object | Shaoqing Ren |
E370248
|
NE FINISHED |
How this triple was built (2 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: Shaoqing Ren | Statement: [Kaiming He, coAuthor, Shaoqing Ren]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shaoqing Ren Context triple: [Kaiming He, coAuthor, Shaoqing Ren]
-
A.
Shaoqing Ren
chosen
Shaoqing Ren is a Chinese computer vision researcher best known as a co-developer of deep learning architectures such as ResNet and Faster R-CNN that have significantly advanced image recognition and object detection.
-
B.
Zhen Luo
Zhen Luo, better known as Empress Zhen of Wei, was a consort of Cao Pi and posthumous empress of the state of Cao Wei during China’s Three Kingdoms period.
-
C.
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.
-
D.
Yanluo Wang
Yanluo Wang is the Chinese deity who presides over the underworld and judges the souls of the dead.
-
E.
Liwen Shao
Liwen Shao is a brilliant and ambitious Chinese businesswoman and technologist in the Pacific Rim universe, known for her pivotal role in developing advanced Jaeger drone technology.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d85a1483788190ad93c2748e8af34b |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e4607408190ab281a7f7a8012d3 |
completed | April 16, 2026, 1:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff1a6991148190b522684b35c07b1a |
completed | May 9, 2026, 11:28 a.m. |
Created at: April 10, 2026, 3:18 a.m.