Triple
T2039022
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Koltsevaya Line |
E44698
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object |
Dobryninskaya
Dobryninskaya is a Moscow Metro station on the circular Koltsevaya Line, known for its Stalinist-era architecture and central location.
|
E268422
|
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: Dobryninskaya | Statement: [Koltsevaya Line, hasStation, Dobryninskaya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dobryninskaya Context triple: [Koltsevaya Line, hasStation, Dobryninskaya]
-
A.
Savyolovskaya
Savyolovskaya is a Moscow Metro station on the Big Circle Line, serving as part of the city’s modern orbital rapid transit network.
-
B.
Voykovskaya
Voykovskaya is a Moscow Metro station serving the Zamoskvoretskaya Line in the northern part of the city.
-
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.
Karamyshevskaya
Karamyshevskaya is a metro station on Moscow’s Big Circle Line, serving the Khoroshyovo-Mnyovniki area of the city.
-
E.
Vorontsovskaya
Vorontsovskaya is a metro station on Moscow’s Big Circle Line serving the southwestern part of the city.
- 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: Dobryninskaya Triple: [Koltsevaya Line, hasStation, Dobryninskaya]
Generated description
Dobryninskaya is a Moscow Metro station on the circular Koltsevaya Line, known for its Stalinist-era architecture and central location.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dobryninskaya Target entity description: Dobryninskaya is a Moscow Metro station on the circular Koltsevaya Line, known for its Stalinist-era architecture and central location.
-
A.
Savyolovskaya
Savyolovskaya is a Moscow Metro station on the Big Circle Line, serving as part of the city’s modern orbital rapid transit network.
-
B.
Voykovskaya
Voykovskaya is a Moscow Metro station serving the Zamoskvoretskaya Line in the northern part of the city.
-
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.
Karamyshevskaya
Karamyshevskaya is a metro station on Moscow’s Big Circle Line, serving the Khoroshyovo-Mnyovniki area of the city.
-
E.
Vorontsovskaya
Vorontsovskaya is a metro station on Moscow’s Big Circle Line serving the southwestern part of the city.
- 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_69a889159ec481908f9e4472d9f480c7 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abb951870481909dbdd8fc8b0c02fe |
completed | March 7, 2026, 5:36 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aef07c3420819097a153052feb1a15 |
completed | March 9, 2026, 4:08 p.m. |
| NEDg | Description generation | batch_69aef6548458819090d60af7ea747ae6 |
completed | March 9, 2026, 4:33 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69aef76715588190b7e66429f049c4a3 |
completed | March 9, 2026, 4:37 p.m. |
Created at: March 4, 2026, 7:39 p.m.