Triple
T2122149
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amu Darya |
E43947
|
entity |
| Predicate | majorCityOnRiver |
P316
|
FINISHED |
| Object | Nukus |
E112105
|
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: Nukus | Statement: [Amu Darya, majorCityOnRiver, Nukus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nukus Context triple: [Amu Darya, majorCityOnRiver, Nukus]
-
A.
Nukus
chosen
Nukus is the capital of the autonomous Republic of Karakalpakstan in western Uzbekistan, known for its remote desert location and the renowned Nukus Museum of Art.
-
B.
Tashkent
Tashkent is the capital and largest city of Uzbekistan, a major cultural and economic hub in Central Asia with deep historical ties to the Islamic world.
-
C.
Karaganda
Karaganda is a large industrial city in central Kazakhstan known for its coal mining industry and Soviet-era history.
-
D.
Kaspiysk
Kaspiysk is a coastal city on the Caspian Sea in the Republic of Dagestan, Russia, known for its industrial base and strategic naval facilities.
-
E.
Karshi
Karshi is a city in southern Uzbekistan known as an important regional center for industry, agriculture, and transportation.
- 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_69a88717cfe48190b7ecdd68c824848a |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abbb51e8088190a1aeafee4e8dff63 |
completed | March 7, 2026, 5:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae58cd22c8819096dfd06d16703bf8 |
completed | March 9, 2026, 5:21 a.m. |
Created at: March 4, 2026, 7:44 p.m.