Triple
T15216189
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | White Sea coast |
E363641
|
entity |
| Predicate | hasPort |
P35
|
FINISHED |
| Object | Severodvinsk |
E156865
|
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: Severodvinsk | Statement: [White Sea coast, hasPort, Severodvinsk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Severodvinsk Context triple: [White Sea coast, hasPort, Severodvinsk]
-
A.
Severodvinsk
chosen
Severodvinsk is a Russian port city on the White Sea, known as a major center for the construction and maintenance of nuclear submarines.
-
B.
Archangelskoye
Archangelskoye is a historic estate and former aristocratic residence near Moscow, Russia, known for its neoclassical palace, landscaped park, and role as a cultural and political retreat.
-
C.
Severomorsk
Severomorsk is a closed naval town in Russia’s Murmansk Oblast that serves as the main base of the Russian (formerly Soviet) Northern Fleet on the Barents Sea.
-
D.
Novo-Arkhangelsk
Novo-Arkhangelsk was the Russian colonial-era name for the settlement that later became the city of Sitka in present-day Alaska.
-
E.
Murmansk
Murmansk is a major Arctic port city in northwestern Russia, known for its ice-free harbor and strategic military and shipping importance.
- 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_69e0076f90c481909989befe031a2cae |
completed | April 15, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff133950288190a5ffeb52ee0bac37 |
completed | May 9, 2026, 10:58 a.m. |
Created at: April 10, 2026, 3:11 a.m.