Triple
T11182681
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sary-Arka Airport |
E264579
|
entity |
| Predicate | serves |
P98
|
FINISHED |
| Object | Karaganda |
E52322
|
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: Karaganda | Statement: [Sary-Arka Airport, serves, Karaganda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Karaganda Context triple: [Sary-Arka Airport, serves, Karaganda]
-
A.
Karaganda
chosen
Karaganda is a large industrial city in central Kazakhstan known for its coal mining industry and Soviet-era history.
-
B.
Kokshetau
Kokshetau is a city in northern Kazakhstan that serves as the administrative and economic center of the surrounding Akmola Region.
-
C.
Syktyvkar
Syktyvkar is the capital city of the Komi Republic in northwestern Russia, known as an administrative, cultural, and economic center of the region.
-
D.
Zhezkazgan
Zhezkazgan is a major industrial and mining city in central Kazakhstan, known especially for its large copper deposits and metallurgical complex.
-
E.
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.
- 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_69d6aa9dafac8190bd90d2c74f661aa7 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8a9c5e081908c85b41a268428fb |
completed | April 9, 2026, 5:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f716adaed081909a6c026f9e232381 |
completed | May 3, 2026, 9:34 a.m. |
Created at: April 8, 2026, 9:29 p.m.