Triple
T22542937
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nanning railway station |
E557341
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Nanning |
—
|
NE NERFINISHED |
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: Nanning | Statement: [Nanning railway station, locatedIn, Nanning]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nanning Context triple: [Nanning railway station, locatedIn, Nanning]
-
A.
Nanning
chosen
Nanning is the capital and largest city of China’s Guangxi Zhuang Autonomous Region, known as a key economic hub and “Green City” in the Lingnan cultural area.
-
B.
Wuzhou
Wuzhou is a prefecture-level city in eastern Guangxi, China, known as a regional transport hub and commercial center along the Xi River.
-
C.
Liuzhou
Liuzhou is a major industrial city in the Guangxi Zhuang Autonomous Region of southern China, known for its heavy industry, transportation hub status, and distinctive karst landscape.
-
D.
Guigang
Guigang is a prefecture-level city in southeastern Guangxi, China, known as a regional transport hub and commercial center along the Xun River.
-
E.
Chongzuo
Chongzuo is a prefecture-level city in southern China’s Guangxi region, known for its karst landscapes and location near the border with Vietnam.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e58662081909ae346ab384514ca |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15f330a40819098df6a9b0f27635e |
completed | April 29, 2026, 1:30 a.m. |
Created at: April 16, 2026, 8:51 p.m.