Triple
T7320927
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sverdlovsk Oblast |
E168541
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object |
Artyomovsky
Artyomovsky is a town in Russia’s Ural region known for its industrial base and role as a local administrative center.
|
E662530
|
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: Artyomovsky | Statement: [Sverdlovsk Oblast, hasCity, Artyomovsky]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Artyomovsky Context triple: [Sverdlovsk Oblast, hasCity, Artyomovsky]
-
A.
Yukhnov
Yukhnov is a small historic town in western Russia known for its location on the Ugra River and its role in regional trade and World War II history.
-
B.
Vyazemsky
Vyazemsky is a small town in Russia’s Far Eastern Federal District, serving as an administrative center within Khabarovsk Krai.
-
C.
Paveletskaya
Paveletskaya is a Moscow Metro station named after the nearby Paveletsky railway terminal, serving as a key transport hub in the city’s network.
-
D.
Kamenskiy
Kamenskiy is a Slavic surname, commonly transliterated from Russian or related languages, borne by various individuals across Eastern Europe and the former Soviet Union.
-
E.
Mishaninskaya
Mishaninskaya is a rural locality in Russia best known as the birthplace of the polymath and scientist Mikhail Lomonosov.
- 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: Artyomovsky Triple: [Sverdlovsk Oblast, hasCity, Artyomovsky]
Generated description
Artyomovsky is a town in Russia’s Ural region known for its industrial base and role as a local administrative center.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Artyomovsky Target entity description: Artyomovsky is a town in Russia’s Ural region known for its industrial base and role as a local administrative center.
-
A.
Yukhnov
Yukhnov is a small historic town in western Russia known for its location on the Ugra River and its role in regional trade and World War II history.
-
B.
Vyazemsky
Vyazemsky is a small town in Russia’s Far Eastern Federal District, serving as an administrative center within Khabarovsk Krai.
-
C.
Paveletskaya
Paveletskaya is a Moscow Metro station named after the nearby Paveletsky railway terminal, serving as a key transport hub in the city’s network.
-
D.
Kamenskiy
Kamenskiy is a Slavic surname, commonly transliterated from Russian or related languages, borne by various individuals across Eastern Europe and the former Soviet Union.
-
E.
Mishaninskaya
Mishaninskaya is a rural locality in Russia best known as the birthplace of the polymath and scientist Mikhail Lomonosov.
- 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_69c68a5251508190ad68df4151cfeb04 |
completed | March 27, 2026, 1:46 p.m. |
| NER | Named-entity recognition | batch_69c6ef1ba58481909cfb5030b85f385a |
completed | March 27, 2026, 8:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c810c6617c8190b4b37466e32c71c0 |
completed | March 28, 2026, 5:32 p.m. |
| NEDg | Description generation | batch_69c814ff89708190a6a626ac204f8c6b |
completed | March 28, 2026, 5:50 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c819174bc48190b5575818ccc2f144 |
completed | March 28, 2026, 6:08 p.m. |
Created at: March 27, 2026, 3:02 p.m.