Triple
T9823693
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wuzhizhou Island |
E238598
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Sanya tourism area |
E238596
|
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: Sanya tourism area | Statement: [Wuzhizhou Island, partOf, Sanya tourism area]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sanya tourism area Context triple: [Wuzhizhou Island, partOf, Sanya tourism area]
-
A.
Sanya
chosen
Sanya is a major resort city on the southern coast of China’s Hainan Island, known for its tropical climate and popular beach tourism.
-
B.
Sanya Bay
Sanya Bay is a popular coastal tourist area in Sanya, Hainan, China, known for its long sandy beaches, tropical scenery, and seaside resorts along the South China Sea.
-
C.
Xingsha
Xingsha is a town in Changsha County, Hunan Province, China, known as the modern urban area closest to the famous Mawangdui Han Tombs archaeological site.
-
D.
Haikou
Haikou is the capital and largest city of China’s Hainan Province, known as a key port, commercial hub, and tropical coastal destination.
-
E.
Xiaomeisha Beach
Xiaomeisha Beach is a popular seaside resort area in Shenzhen, China, known for its sandy shoreline, recreational facilities, and coastal scenery.
- 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_69ca84e0dd1881909800765d1e21f735 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb316f8948190ada3738787a5cb6a |
completed | April 2, 2026, 12:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1cc810bac8190a5ff94c0717e7706 |
completed | April 5, 2026, 2:44 a.m. |
Created at: March 30, 2026, 8:31 p.m.