Triple
T11570162
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shaoshan City |
E274363
|
entity |
| Predicate | romanization |
P2508
|
FINISHED |
| Object | Shaoshan |
E42100
|
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: Shaoshan | Statement: [Shaoshan City, romanization, Shaoshan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shaoshan Context triple: [Shaoshan City, romanization, Shaoshan]
-
A.
Shaoshan
chosen
Shaoshan is a town in Hunan Province, China, best known as the birthplace of Mao Zedong and a significant site of modern Chinese revolutionary history.
-
B.
Shaoshan Peak
Shaoshan Peak is a prominent mountain summit in China’s Shaoshan region, known for its natural scenery and cultural significance as part of the birthplace area of Mao Zedong.
-
C.
Mao Ling
Mao Ling is the mausoleum complex that serves as the imperial tomb of the Ming dynasty Chenghua Emperor in China.
-
D.
Yixian
Yixian is a historic county-level city in China’s Anhui province, noted for its well-preserved ancient villages and traditional Huizhou architecture.
-
E.
Yuanpei
Yuanpei is the given name of Cai Yuanpei, a prominent Chinese educator and reformer who served as president of Peking University in the early 20th century.
- 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_69d6aae5ac3c81908d2b0a3a665665b2 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d88dd543a48190b834abd8e8ae7b65 |
completed | April 10, 2026, 5:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e6e8dec908819080d97cd33be55b3f |
completed | April 21, 2026, 3:02 a.m. |
Created at: April 8, 2026, 9:37 p.m.