Triple
T11489749
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Xiangtan County |
E272373
|
entity |
| Predicate | province |
P604
|
FINISHED |
| Object | Hunan |
E30061
|
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: Hunan | Statement: [Xiangtan County, province, Hunan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hunan Context triple: [Xiangtan County, province, Hunan]
-
A.
Hunan Province
chosen
Hunan Province is a landlocked region in south-central China known for its strategic location, spicy cuisine, and role as a major battleground and revolutionary base in modern Chinese history.
-
B.
Hubei Province
Hubei Province is a landlocked region in central China known for its capital city Wuhan, major role in industry and transportation, and significant historical and cultural heritage.
-
C.
Bié Province
Bié Province is a central Angolan province known for its highland terrain, agricultural activity, and strategic location bordering several other provinces.
-
D.
Kansu
Kansu is a Turkish surname most notably associated with Şevket Aziz Kansu, a prominent Turkish academic and anthropologist.
-
E.
northwestern Hunan
Northwestern Hunan is a subregion of China’s Hunan Province characterized by its inland location, river plains, and a mix of urban centers and agricultural areas.
- 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_69d6aae1b09881909ce2ded3fa0c14fa |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d85a20df608190992543b4d7006f8a |
completed | April 10, 2026, 2:02 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e624c3691081908f2e448aebab40aa |
completed | April 20, 2026, 1:06 p.m. |
Created at: April 8, 2026, 9:36 p.m.