Triple
T8407286
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cao Rui |
E198530
|
entity |
| Predicate | mother |
P120
|
FINISHED |
| Object |
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.
|
E738356
|
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: Zhen Luo | Statement: [Cao Rui, mother, Zhen Luo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zhen Luo Context triple: [Cao Rui, mother, Zhen Luo]
-
A.
Zhe-Xi Luo
Zhe-Xi Luo is a paleontologist known for his research on early mammals and mammalian evolution, including the study and description of important fossil species.
-
B.
Yanluo Wang
Yanluo Wang is the Chinese deity who presides over the underworld and judges the souls of the dead.
-
C.
Shaoqing Ren
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.
-
D.
Jun-Yan Zhu
Jun-Yan Zhu is a computer scientist and researcher known for his influential work in computer vision and generative models, particularly in image-to-image translation.
-
E.
Xing Li
Xing Li is a computer networking expert known for co-authoring IETF standards, including RFC 6145 on IPv4/IPv6 translation mechanisms.
- 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: Zhen Luo Triple: [Cao Rui, mother, Zhen Luo]
Generated description
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.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Zhen Luo Target entity description: 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.
-
A.
Zhe-Xi Luo
Zhe-Xi Luo is a paleontologist known for his research on early mammals and mammalian evolution, including the study and description of important fossil species.
-
B.
Yanluo Wang
Yanluo Wang is the Chinese deity who presides over the underworld and judges the souls of the dead.
-
C.
Shaoqing Ren
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.
-
D.
Jun-Yan Zhu
Jun-Yan Zhu is a computer scientist and researcher known for his influential work in computer vision and generative models, particularly in image-to-image translation.
-
E.
Xing Li
Xing Li is a computer networking expert known for co-authoring IETF standards, including RFC 6145 on IPv4/IPv6 translation mechanisms.
- 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_69ca8310df9c8190b25f16161cca3e41 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cb831409308190981089c303ebaef4 |
completed | March 31, 2026, 8:17 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce4db075c881909083b3384fcde344 |
completed | April 2, 2026, 11:06 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, 6:05 p.m.