Triple

T2852856
Position Surface form Disambiguated ID Type / Status
Subject Arkhangelsk Oblast E63131 entity
Predicate administrativeCenter P1474 FINISHED
Object Arkhangelsk E101428 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: Arkhangelsk | Statement: [Arkhangelsk Oblast, administrativeCenter, Arkhangelsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Arkhangelsk
Context triple: [Arkhangelsk Oblast, administrativeCenter, Arkhangelsk]
  • A. Arkhangelsk chosen
    Arkhangelsk is a historic port city in northern Russia on the White Sea, long serving as a key maritime gateway and administrative center of the surrounding region.
  • B. Murmansk
    Murmansk is a major Arctic port city in northwestern Russia, known for its ice-free harbor and strategic military and shipping importance.
  • C. Severodvinsk
    Severodvinsk is a Russian port city on the White Sea, known as a major center for the construction and maintenance of nuclear submarines.
  • D. Tomsk
    Tomsk is a historic university and research city in southwestern Siberia, known as one of the region’s oldest and most important cultural and educational centers.
  • E. Kirov
    Kirov is the revolutionary pseudonym of Sergei Kirov, a prominent early Soviet political leader and close associate of Joseph Stalin.
  • 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_69ab4c407c408190857d25e027155ce9 completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abdf5e043c8190ac82112abce7262a completed March 7, 2026, 8:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69b08644192481909cb5ec394148adf4 completed March 10, 2026, 8:59 p.m.
Created at: March 6, 2026, 10:02 p.m.