Triple
T19986540
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Suihua |
E493946
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Yichun |
—
|
NE NERFINISHED |
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: Yichun | Statement: [Suihua, borderedBy, Yichun]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yichun Context triple: [Suihua, borderedBy, Yichun]
-
A.
Yichun
Yichun is a prefecture-level city in western Jiangxi Province, China, known for its natural scenery, hot springs, and cultural heritage.
-
B.
Yichun
chosen
Yichun is a forest-rich prefecture-level city in northeastern China known for its extensive woodland resources and cold climate.
-
C.
Chenzhou
Chenzhou is a prefecture-level city in southern Hunan Province, China, known as a regional transport hub and for its rich mineral resources and scenic mountainous landscapes.
-
D.
Jishou
Jishou is a county-level city in western Hunan, China, known as the political, economic, and cultural center of the Xiangxi region.
-
E.
Ganzhou
Ganzhou is a major prefecture-level city in southern Jiangxi Province, China, known as a regional economic and transportation hub with a long history and rich cultural heritage.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da626a67648190af9653832a3aeced |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e65d16f60c81909ba02c0a3429ecae |
completed | April 20, 2026, 5:06 p.m. |
Created at: April 11, 2026, 3:29 p.m.