Triple
T16980101
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Military Institute of Land Forces of Kazakhstan |
E411920
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Almaty |
E50745
|
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: Almaty | Statement: [Military Institute of Land Forces of Kazakhstan, locatedIn, Almaty]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Almaty Context triple: [Military Institute of Land Forces of Kazakhstan, locatedIn, Almaty]
-
A.
Almaty
chosen
Almaty is the largest city and main commercial and cultural center of Kazakhstan, located in the country’s mountainous southeast.
-
B.
Karaganda
Karaganda is a large industrial city in central Kazakhstan known for its coal mining industry and Soviet-era history.
-
C.
Shymkent
Shymkent is one of the largest and most populous cities in southern Kazakhstan, serving as a key industrial, commercial, and cultural center of the region.
-
D.
Nur-Sultan
Nur-Sultan is the planned capital city of Kazakhstan, known for its rapid modern development and distinctive futuristic architecture.
-
E.
Zhezkazgan
Zhezkazgan is a major industrial and mining city in central Kazakhstan, known especially for its large copper deposits and metallurgical complex.
- 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_69d886ca8f348190812768ea8d5055ce |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d1866bf48190a0ea15c377bf782c |
completed | April 18, 2026, 6:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00dc0d437c81908f003a10b798998a |
completed | May 10, 2026, 7:27 p.m. |
Created at: April 10, 2026, 5:32 a.m.