Triple
T10109926
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | hsn |
E218212
|
entity |
| Predicate | hasDialect |
P4251
|
FINISHED |
| Object | Ningxiang Xiang |
E180955
|
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: Ningxiang Xiang | Statement: [hsn, hasDialect, Ningxiang Xiang]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ningxiang Xiang Context triple: [hsn, hasDialect, Ningxiang Xiang]
-
A.
Ningxiang
chosen
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.
-
B.
Xinshao Xiang
Xinshao Xiang is a regional variety of the Xiang Chinese language spoken primarily in Xinshao County, Hunan Province, China.
-
C.
Pingxiang
Pingxiang is a prefecture-level industrial city in western Jiangxi Province, China, known historically for its coal mining and ceramics production.
-
D.
Xiangxiang City
Xiangxiang City is a county-level city in Hunan Province, China, administered by the prefecture-level city of Xiangtan and known for its historical and cultural heritage.
-
E.
Dongkou Xiang
Dongkou Xiang is a regional variety of the Xiang Chinese language spoken in and around Dongkou County in Hunan Province, China.
- 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_69d90d54c32c8190b175a30c7c905cd2 |
completed | April 10, 2026, 2:46 p.m. |
Created at: March 30, 2026, 9:03 p.m.