Triple
T7315672
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Younan Xia |
E168405
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Younan Xia |
E168405
|
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: Younan Xia | Statement: [Younan Xia, name, Younan Xia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Younan Xia Context triple: [Younan Xia, name, Younan Xia]
-
A.
Younan Xia
chosen
Younan Xia is a prominent chemist and materials scientist known for his pioneering work in nanomaterials synthesis and nanotechnology.
-
B.
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.
-
C.
Xiong Yi
Xiong Yi was the legendary early ruler credited with establishing the ancient Chinese state of Chu during the Zhou dynasty.
-
D.
Yao Chen
Yao Chen is a prominent Chinese actress and philanthropist known for her influential social media presence and advocacy on social issues.
-
E.
Yu Xuezhong
Yu Xuezhong was a prominent Chinese military leader associated with the Northeastern Army during the Republican era.
- 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_69c68a5251508190ad68df4151cfeb04 |
completed | March 27, 2026, 1:46 p.m. |
| NER | Named-entity recognition | batch_69c6ec04bdfc819093556aa5fa69e0e1 |
completed | March 27, 2026, 8:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c81eb9c46881908da8fde17a09b50d |
completed | March 28, 2026, 6:32 p.m. |
Created at: March 27, 2026, 3:02 p.m.