Triple
T6843628
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Huangshan (city) |
E157836
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Qimen County |
E404176
|
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: Qimen County | Statement: [Huangshan (city), contains, Qimen County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Qimen County Context triple: [Huangshan (city), contains, Qimen County]
-
A.
Qimen County
chosen
Qimen County is a region in Anhui Province, China, internationally renowned as the birthplace of Keemun black tea.
-
B.
Yingshang County
Yingshang County is an administrative county in Anhui Province, China, governed by the prefecture-level city of Fuyang.
-
C.
Minqing County
Minqing County is an administrative county under the jurisdiction of Fuzhou in Fujian Province, southeastern China, known for its mountainous terrain and traditional rural communities.
-
D.
Linquan County
Linquan County is an administrative county in western Anhui Province, China, governed by the prefecture-level city of Fuyang.
-
E.
Guanyun County
Guanyun County is an administrative county under the jurisdiction of Lianyungang City in Jiangsu Province, eastern China, known for its agricultural production and location near the Yellow Sea coast.
- 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_69c6882ed4c081909dc465a7cf8838be |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d6b7179481909e3482fef47b2719 |
completed | March 27, 2026, 7:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7bf6c62948190a8e8f0d8f259ba42 |
completed | March 28, 2026, 11:45 a.m. |
Created at: March 27, 2026, 2:19 p.m.