Triple
T10109923
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | hsn |
E218212
|
entity |
| Predicate | hasDialect |
P4251
|
FINISHED |
| Object |
Suining Xiang
Suining Xiang is a regional variety of the Xiang group of Chinese dialects spoken in and around Suining in Hunan Province, China.
|
E846087
|
NE FINISHED |
How this triple was built (4 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: Suining Xiang | Statement: [hsn, hasDialect, Suining Xiang]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Suining Xiang Context triple: [hsn, hasDialect, Suining Xiang]
-
A.
Xiuning
Xiuning is a county-level city in Anhui Province, China, known for its traditional Huizhou culture, historic architecture, and scenic mountainous landscapes.
-
B.
Xianning
Xianning is a prefecture-level city in southeastern Hubei Province, China, known for its hot springs, karst landscapes, and historical sites.
-
C.
Zhongmou
Zhongmou is the courtesy name of Sun Quan, the founding emperor of Eastern Wu during China’s Three Kingdoms period.
-
D.
Tongxiang
Tongxiang is a county-level city in northern Zhejiang Province, China, known for administering the historic water town of Wuzhen.
-
E.
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.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Suining Xiang Triple: [hsn, hasDialect, Suining Xiang]
Generated description
Suining Xiang is a regional variety of the Xiang group of Chinese dialects spoken in and around Suining in Hunan Province, China.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Suining Xiang Target entity description: Suining Xiang is a regional variety of the Xiang group of Chinese dialects spoken in and around Suining in Hunan Province, China.
-
A.
Xiuning
Xiuning is a county-level city in Anhui Province, China, known for its traditional Huizhou culture, historic architecture, and scenic mountainous landscapes.
-
B.
Xianning
Xianning is a prefecture-level city in southeastern Hubei Province, China, known for its hot springs, karst landscapes, and historical sites.
-
C.
Zhongmou
Zhongmou is the courtesy name of Sun Quan, the founding emperor of Eastern Wu during China’s Three Kingdoms period.
-
D.
Tongxiang
Tongxiang is a county-level city in northern Zhejiang Province, China, known for administering the historic water town of Wuzhen.
-
E.
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.
- F. None of above. chosen
Provenance (5 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. |
| NEDg | Description generation | batch_69d3028994fc81908507449a10e7e093 |
completed | April 6, 2026, 12:47 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d3031ed1e88190b9906338285a6e46 |
completed | April 6, 2026, 12:49 a.m. |
Created at: March 30, 2026, 9:03 p.m.