Triple
T17664397
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mi River |
E440336
|
entity |
| Predicate | riverSystem |
P1009
|
FINISHED |
| Object | Xiang River system |
—
|
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: Xiang River system | Statement: [Mi River, riverSystem, Xiang River system]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Xiang River system Context triple: [Mi River, riverSystem, Xiang River system]
-
A.
Xiang River
The Xiang River is a major waterway in southern China that flows through Hunan province and has historically been an important route for transport, culture, and military campaigns.
-
B.
Xiang River basin
chosen
The Xiang River basin is a major river system in southern China that drains much of Hunan Province and has long been a vital corridor for agriculture, transport, and regional culture.
-
C.
Taizi River
The Taizi River is a major river in northeastern China that flows through Liaoning Province, including the city of Benxi, and serves as an important regional waterway.
-
D.
Xiangxi River
The Xiangxi River is a tributary waterway in China that feeds into the Jialing River within the upper Yangtze River basin.
-
E.
Luhan River
The Luhan River is a waterway in eastern Ukraine that flows through the Luhansk region, including the town of Slavyanoserbsk.
- 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_69d8b9e87e18819087104a44dc4dc5b1 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e46ea7f0ec81908eff43aa845584af |
completed | April 19, 2026, 5:56 a.m. |
Created at: April 10, 2026, 9:54 a.m.