Triple
T2684719
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guizhou Province |
E57456
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object | 黔 |
E57456
|
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: 黔 | Statement: [Guizhou Province, abbreviation, 黔]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 黔 Context triple: [Guizhou Province, abbreviation, 黔]
-
A.
Guizhou Province
chosen
Guizhou Province is a mountainous, ethnically diverse region in southwest China known for its karst landscapes, cool climate, and rapid economic development.
-
B.
川
川 is the commonly used single-character Chinese abbreviation for Sichuan Province.
-
C.
Zhaotong
Zhaotong is a prefecture-level city in northeastern Yunnan Province, China, known as a transport hub and gateway between Yunnan and the neighboring provinces of Sichuan and Guizhou.
-
D.
Guiyang
Guiyang is the capital city of Guizhou Province in southwest China, known for its cool climate, karst landscapes, and role as a regional transportation and industrial hub.
-
E.
苏
苏 is the standard Chinese abbreviation used to refer to Jiangsu Province in eastern 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_69ab4a5028388190a36f3baf1588309e |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd9edba5c8190b86d6cba0f1964e2 |
completed | March 7, 2026, 7:55 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afa0700d548190944544495a2d42f6 |
completed | March 10, 2026, 4:39 a.m. |
Created at: March 6, 2026, 9:54 p.m.