Triple
T3678915
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coquimbo |
E78061
|
entity |
| Predicate | twinCity |
P1072
|
FINISHED |
| Object | Beihai |
E56871
|
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: Beihai | Statement: [Coquimbo, twinCity, Beihai]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beihai Context triple: [Coquimbo, twinCity, Beihai]
-
A.
Beihai
chosen
Beihai is a coastal city in China's Guangxi Zhuang Autonomous Region, known for its beaches, maritime trade, and the scenic Silver Beach tourist area.
-
B.
Beibu Wan
Beibu Wan is the Chinese name for the Gulf of Tonkin, a large body of water in the South China Sea bordered by China and Vietnam.
-
C.
Wanning
Wanning is a county-level coastal city in southeastern Hainan, China, known for its tropical climate, beaches, and surf-friendly bays.
-
D.
Nanhai
Nanhai is an alternative name for Nanhai Lake, a notable body of water often associated with scenic and cultural significance in its region.
-
E.
Chuansha
Chuansha is a subdistrict in Shanghai’s Pudong New Area known for its blend of traditional town features and rapidly developing urban infrastructure.
- 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_69ad85e18c1c8190be8aafb227f39f48 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc46599188190a046eddb0d85c483 |
completed | March 8, 2026, 6:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4c3a9c6f48190a44b3b2dab37268d |
completed | March 14, 2026, 2:10 a.m. |
Created at: March 8, 2026, 3:25 p.m.