Triple
T11489792
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Xiangxiang City |
E272374
|
entity |
| Predicate | hasChineseName |
P4878
|
FINISHED |
| Object | 湘乡市 |
E272374
|
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: 湘乡市 | Statement: [Xiangxiang City, hasChineseName, 湘乡市]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 湘乡市 Context triple: [Xiangxiang City, hasChineseName, 湘乡市]
-
A.
浏阳
浏阳是中国湖南省东部的一座县级市，以烟花爆竹产业和红色革命历史而闻名。
-
B.
Xiangtan County
Xiangtan County is an administrative county in Hunan Province, China, governed by the prefecture-level city of Xiangtan and known for its role in the region’s agricultural and industrial economy.
-
C.
Xiangxiang City
chosen
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.
-
D.
Changsha County
Changsha County is an administrative division of Hunan Province in south-central China that encompasses the area served by Changsha Huanghua International Airport.
-
E.
Zixing City
Zixing City is a county-level city in Hunan Province, China, administered by the prefecture-level city of Chenzhou and known for its mountainous landscapes and mining industry.
- 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_69e6046ec5108190a0294cc86e1b60cc |
completed | April 20, 2026, 10:48 a.m. |
Created at: April 8, 2026, 9:36 p.m.