Triple

T15460702
Position Surface form Disambiguated ID Type / Status
Subject Monchegorsk E371889 entity
Predicate near 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: [Monchegorsk, near, Apatity]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Apatity
Context triple: [Monchegorsk, near, 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_69d85cc8bd308190886949510b42e764 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03f17663c8190b995c7c3129c90d6 completed April 16, 2026, 1:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff56b6f3dc81909a97913da6b739bd completed May 9, 2026, 3:45 p.m.
Created at: April 10, 2026, 3:32 a.m.