Triple
T8727793
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Feng Guozhang |
E207173
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Feng |
E206051
|
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: Feng | Statement: [Feng Guozhang, familyName, Feng]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Feng Context triple: [Feng Guozhang, familyName, Feng]
-
A.
Feng
chosen
Feng is a Chinese surname borne by various notable figures in Chinese history and culture.
-
B.
Feng
Feng was an early capital city of the Zhou dynasty in ancient China, serving as a key political and cultural center before later relocations.
-
C.
Shenfeng
Shenfeng was a historical Chinese era name used during the reign of Sun Quan, ruler of Eastern Wu in the Three Kingdoms period.
-
D.
Sulamutag Feng
Sulamutag Feng is the highest peak in China’s remote Altyn-Tagh mountain range on the northern edge of the Tibetan Plateau.
-
E.
Feng Qingfeng
Feng Qingfeng is a Chinese automotive executive known for leading and overseeing strategic direction at the British sports car manufacturer Lotus Cars.
- 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_69ca8358e4008190898471a59b96c301 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5d1890e0819088b271db51faa738 |
completed | March 31, 2026, 11:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf291b737481909a90e482273c5f76 |
completed | April 3, 2026, 2:42 a.m. |
Created at: March 30, 2026, 6:37 p.m.