Triple
T10110057
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Old Xiang |
E218215
|
entity |
| Predicate | hasDialects |
P4251
|
FINISHED |
| Object | Loudi Old Xiang |
E175006
|
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: Loudi Old Xiang | Statement: [Old Xiang, hasDialects, Loudi Old Xiang]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Loudi Old Xiang Context triple: [Old Xiang, hasDialects, Loudi Old Xiang]
-
A.
Liling Xiang
Liling Xiang is a regional Chinese dialect spoken in and around Liling in Hunan Province.
-
B.
Loudi
chosen
Loudi is a prefecture-level city in south-central China known for its role as an industrial and transportation hub within Hunan Province.
-
C.
Anhua Xiang
Anhua Xiang is a regional variety of the Xiang Chinese language spoken primarily in Anhua County, Hunan Province, China.
-
D.
Ningxiang
Ningxiang is a county-level city in Hunan Province, China, administered by the prefecture-level city of Changsha and known for its rapidly developing economy and rich cultural heritage.
-
E.
Pingxiang
Pingxiang is a prefecture-level industrial city in western Jiangxi Province, China, known historically for its coal mining and ceramics production.
- 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_69ca83da93fc8190b54e44bc2b34857c |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cdd0cdb3c88190a74f75bf865664f3 |
completed | April 2, 2026, 2:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d3005e007881909f40575d129f2c3d |
completed | April 6, 2026, 12:37 a.m. |
Created at: March 30, 2026, 9:03 p.m.