Triple
T10043792
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yuan River |
E205359
|
entity |
| Predicate | majorCityOnRiver |
P316
|
FINISHED |
| Object | Huaihua |
E178994
|
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: Huaihua | Statement: [Yuan River, majorCityOnRiver, Huaihua]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Huaihua Context triple: [Yuan River, majorCityOnRiver, Huaihua]
-
A.
Huaihua
chosen
Huaihua is a prefecture-level city in southwestern Hunan Province, China, known as a regional transportation hub and home to several ethnic minority communities.
-
B.
Hengyang
Hengyang is a major industrial and transportation hub city in southern China, located along the Xiang River in the south of Hunan Province.
-
C.
Yongzhou
Yongzhou is a prefecture-level city in southern Hunan Province, China, known for its long history and location at the confluence of the Xiang and Xiao rivers.
-
D.
Shaoyang
Shaoyang is a prefecture-level city in south-central China known for its long history, cultural heritage, and location in the southwestern part of Hunan Province.
-
E.
Jishou
Jishou is a county-level city in western Hunan, China, known as the political, economic, and cultural center of the Xiangxi region.
- 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_69ca834f70e88190b2d74828b7767ec1 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cdcf61b3e08190b69bcf67b6a95342 |
completed | April 2, 2026, 2:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2e559a1608190903e9b2dff12bb00 |
completed | April 5, 2026, 10:42 p.m. |
Created at: March 30, 2026, 8:55 p.m.