Triple
T20499871
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kashkadarya River |
E503271
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | Karshi |
—
|
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: Karshi | Statement: [Kashkadarya River, flowsThrough, Karshi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Karshi Context triple: [Kashkadarya River, flowsThrough, Karshi]
-
A.
Karshi
chosen
Karshi is a city in southern Uzbekistan known as an important regional center for industry, agriculture, and transportation.
-
B.
Karaganda
Karaganda is a large industrial city in central Kazakhstan known for its coal mining industry and Soviet-era history.
-
C.
Shamkir
Shamkir is a town in western Azerbaijan known as a regional center with historical significance and a growing agricultural and industrial economy.
-
D.
Andijan
Andijan is a historic city in eastern Uzbekistan, known as a major cultural and economic center of the Fergana Valley and as the birthplace of the Mughal emperor Babur.
-
E.
Kazanh
Kazanh is a locality within Turkey’s Ankara Province, situated in the Central Anatolia region.
- 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_69e0b4b1e52c8190894281cf7e3283ab |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69cc10cd08190915b6c29c6473f77 |
completed | April 20, 2026, 9:38 p.m. |
Created at: April 16, 2026, 11:35 a.m.