Triple
T15216057
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Khibiny Mountains |
E363638
|
entity |
| Predicate | nearCity |
P350
|
FINISHED |
| Object | Apatity |
E368625
|
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: Apatity | Statement: [Khibiny Mountains, nearCity, Apatity]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Apatity Context triple: [Khibiny Mountains, nearCity, Apatity]
-
A.
Apatity
chosen
Apatity is an industrial and scientific town in Russia’s Murmansk Oblast, known for its phosphate mining and research institutes within the Arctic Kola Peninsula region.
-
B.
Salekhard
Salekhard is a Russian Arctic city located on the Ob River and notable as the only city in the world situated directly on the Arctic Circle.
-
C.
Yakutsk
Yakutsk is a major city in northeastern Siberia, Russia, known as one of the coldest large cities in the world and a key administrative and cultural center of the Sakha Republic.
-
D.
Angarsk
Angarsk is a major industrial city in southeastern Siberia, Russia, known for its petrochemical and nuclear-related facilities.
-
E.
Norilsk
Norilsk is a remote industrial city in northern Siberia, Russia, known for its massive nickel and palladium mining operations, extreme Arctic climate, and severe environmental pollution.
- 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_69d85a0b78bc8190b6e5ad51a2c4cfc5 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0076e4348819091fa91c1562e7c5c |
completed | April 15, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fef88f8ac881908ca32de44b5aa53a |
completed | May 9, 2026, 9:04 a.m. |
Created at: April 10, 2026, 3:11 a.m.