Triple
T8219638
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nan’an District |
E192024
|
entity |
| Predicate | hasPinyinName |
P2508
|
FINISHED |
| Object | Nán’àn Qū |
E426395
|
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: Nán’àn Qū | Statement: [Nan’an District, hasPinyinName, Nán’àn Qū]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nán’àn Qū Context triple: [Nan’an District, hasPinyinName, Nán’àn Qū]
-
A.
Nánníng
Nánníng is the capital and largest city of China’s Guangxi Zhuang Autonomous Region, known as a major economic hub and “Green City” for its abundant subtropical vegetation.
-
B.
Jiànyè Qū
Jiànyè Qū is the Hanyu Pinyin romanized name for Jianye District, an urban district of Nanjing in Jiangsu Province, China.
-
C.
Guanggu
Guanggu is a major high-tech development zone in Wuhan, China, known as an innovation hub for the optics and electronics industries.
-
D.
Nan’an
chosen
Nan’an is a county-level city administered by Quanzhou in Fujian Province, China, known for its historical ties to maritime trade and its rapidly developing manufacturing economy.
-
E.
Huai-an
Huai-an is an older romanized spelling of Huaian, a prefecture-level city in Jiangsu Province, China, known for its historical significance and canal-based waterways.
- 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_69ca82c9a8ac81908b011c38698456e4 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb7772b76c8190b1952650c736eb91 |
completed | March 31, 2026, 7:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ccee01ed9c819086bfc35e89f7bad8 |
completed | April 1, 2026, 10:05 a.m. |
Created at: March 30, 2026, 5:45 p.m.