Triple
T12910480
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tselinograd |
E308846
|
entity |
| Predicate | predecessorName |
P11166
|
FINISHED |
| Object | Akmolinsk |
E276106
|
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: Akmolinsk | Statement: [Tselinograd, predecessorName, Akmolinsk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Akmolinsk Context triple: [Tselinograd, predecessorName, Akmolinsk]
-
A.
Akmolinsk
chosen
Akmolinsk is the former name of Kazakhstan’s capital city, now known as Astana.
-
B.
Ust-Kamenogorsk
Ust-Kamenogorsk is an industrial city in northeastern Kazakhstan, known as a major center for metallurgy and winter sports.
-
C.
Kireyevsk
Kireyevsk is a small industrial town in western Russia known for its coal-mining history and location within the Tula region.
-
D.
Karachayevsk
Karachayevsk is a town in southwestern Russia located in the North Caucasus region, serving as one of the main urban centers of the Karachay-Cherkess Republic.
-
E.
Angarsk
Angarsk is a major industrial city in southeastern Siberia, Russia, known for its petrochemical and nuclear-related 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_69d7bdf92b588190acdf2a2291ac4590 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9719e584c81909be1ac1366effca0 |
completed | April 10, 2026, 9:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f70a1a97748190992fe28c6411c4de |
completed | May 3, 2026, 8:40 a.m. |
Created at: April 9, 2026, 5:41 p.m.