Triple
T19900552
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sakhalin Time |
E478273
|
entity |
| Predicate | usedIn |
P98
|
FINISHED |
| Object | Kholmsk |
—
|
NE NERFINISHED |
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: Kholmsk | Statement: [Sakhalin Time, usedIn, Kholmsk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kholmsk Context triple: [Sakhalin Time, usedIn, Kholmsk]
-
A.
Kholmsk
chosen
Kholmsk is a port town on the western coast of Sakhalin Island in Russia, serving as an important maritime transport hub in the Sea of Japan.
-
B.
Kholmogory
Kholmogory is a historic Russian town in the Arkhangelsk region that served as an important early northern trading and administrative center.
-
C.
Krasnoufimsk
Krasnoufimsk is a small historic town in Russia’s Ural region, known for its traditional architecture and role as a local administrative and cultural center.
-
D.
Ozersk
Ozersk is a closed Russian city in Chelyabinsk Oblast known for its nuclear industry and association with the Mayak production facility.
-
E.
Degtyarsk
Degtyarsk is a small industrial town in Russia’s Sverdlovsk Oblast, historically known for its mining activities.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e520682081909892916424699bd5 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65940cf8c8190b74e51635410e48a |
completed | April 20, 2026, 4:50 p.m. |
Created at: April 10, 2026, 1:52 p.m.