Triple
T17532446
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Northern Zhou |
E426969
|
entity |
| Predicate | regent |
P6804
|
FINISHED |
| Object | Yuwen Hu |
—
|
NE NERFINISHED |
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: Yuwen Hu | Statement: [Northern Zhou, regent, Yuwen Hu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yuwen Hu Context triple: [Northern Zhou, regent, Yuwen Hu]
-
A.
Yuwen Hu
chosen
Yuwen Hu was a powerful 6th-century regent and statesman of the Western Wei and Northern Zhou dynasties who effectively controlled the imperial government and orchestrated the rise of the Northern Zhou.
-
B.
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.
-
C.
Yuxin Peng
Yuxin Peng is a computer vision and machine learning researcher known for coauthoring influential papers alongside leading figures such as Shaoqing Ren.
-
D.
Yunxiang Yan
Yunxiang Yan is a prominent anthropologist and scholar of contemporary Chinese society, known for his influential ethnographic studies on rural China, family life, and social change.
-
E.
Ziyu Wang
Ziyu Wang is a machine learning researcher best known for co-developing the dueling deep Q-network (Dueling DQN) architecture in deep reinforcement learning.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d889de677081909b22d2657b1f0292 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e453695734819092d4dcbab4a4fa01 |
completed | April 19, 2026, 4 a.m. |
Created at: April 10, 2026, 5:49 a.m.