Triple

T1138772
Position Surface form Disambiguated ID Type / Status
Subject Zlín E23399 entity
Predicate twinCity P1072 FINISHED
Object Severodvinsk
Severodvinsk is a Russian port city on the White Sea, known as a major center for the construction and maintenance of nuclear submarines.
 E156865 NE FINISHED

How this triple was built (4 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: Severodvinsk | Statement: [Zlín, twinCity, Severodvinsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Severodvinsk
Context triple: [Zlín, twinCity, Severodvinsk]
  • A. Novo-Arkhangelsk
    Novo-Arkhangelsk was the Russian colonial-era name for the settlement that later became the city of Sitka in present-day Alaska.
  • 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. Arkhangelsk
    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.
  • D. Magadan
    Magadan is a remote port city in Russia’s Far East, known historically as a gateway to the Kolyma region and its former Gulag labor camps.
  • E. Kirkenes
    Kirkenes is a remote Arctic town in northeastern Norway, near the Russian border, known for its Barents Sea port, winter tourism, and role as a gateway to the far north.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Severodvinsk
Triple: [Zlín, twinCity, Severodvinsk]
Generated description
Severodvinsk is a Russian port city on the White Sea, known as a major center for the construction and maintenance of nuclear submarines.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Severodvinsk
Target entity description: Severodvinsk is a Russian port city on the White Sea, known as a major center for the construction and maintenance of nuclear submarines.
  • A. Novo-Arkhangelsk
    Novo-Arkhangelsk was the Russian colonial-era name for the settlement that later became the city of Sitka in present-day Alaska.
  • 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. Arkhangelsk
    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.
  • D. Magadan
    Magadan is a remote port city in Russia’s Far East, known historically as a gateway to the Kolyma region and its former Gulag labor camps.
  • E. Kirkenes
    Kirkenes is a remote Arctic town in northeastern Norway, near the Russian border, known for its Barents Sea port, winter tourism, and role as a gateway to the far north.
  • F. None of above. chosen

Provenance (5 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_69a493ef399c8190b04b9146d2314f59 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4bc25dda481909a26d726fdbdbb50 completed March 1, 2026, 10:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69acce57fbe081908a2060344c19141d completed March 8, 2026, 1:18 a.m.
NEDg Description generation batch_69acd06d000481909f6d934e857236f0 completed March 8, 2026, 1:27 a.m.
NED2 Entity disambiguation (via description) batch_69acd17b8c508190812b241d7906992b completed March 8, 2026, 1:31 a.m.
Created at: March 1, 2026, 7:44 p.m.