Triple
T16968139
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vyborgsky District, Saint Petersburg |
E411595
|
entity |
| Predicate | hasMetroStation |
P522
|
FINISHED |
| Object |
Ozerki station
Ozerki station is a Saint Petersburg Metro station serving the Vyborgsky District in the northern part of the city.
|
E1246624
|
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: Ozerki station | Statement: [Vyborgsky District, Saint Petersburg, hasMetroStation, Ozerki station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ozerki station Context triple: [Vyborgsky District, Saint Petersburg, hasMetroStation, Ozerki station]
-
A.
Frunzenskaya station
Frunzenskaya station is a Moscow Metro station known for its deep-level construction and classic Soviet-era architectural design.
-
B.
Obelya station
Obelya station is a metro station in Sofia, Bulgaria, serving as an interchange point between lines of the Sofia Metro network.
-
C.
Nadezhda station
Nadezhda station is a metro station on the Sofia Metro system in Sofia, Bulgaria, serving the Nadezhda residential district.
-
D.
Kachinskaya station
Kachinskaya station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
-
E.
Zhdanovskaya station
Zhdanovskaya station is a former terminus station on the Moscow Metro’s Taganskaya–Zhdanovskaya line, historically serving as an endpoint for trains on that route.
- 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: Ozerki station Triple: [Vyborgsky District, Saint Petersburg, hasMetroStation, Ozerki station]
Generated description
Ozerki station is a Saint Petersburg Metro station serving the Vyborgsky District in the northern part of the city.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ozerki station Target entity description: Ozerki station is a Saint Petersburg Metro station serving the Vyborgsky District in the northern part of the city.
-
A.
Frunzenskaya station
Frunzenskaya station is a Moscow Metro station known for its deep-level construction and classic Soviet-era architectural design.
-
B.
Obelya station
Obelya station is a metro station in Sofia, Bulgaria, serving as an interchange point between lines of the Sofia Metro network.
-
C.
Nadezhda station
Nadezhda station is a metro station on the Sofia Metro system in Sofia, Bulgaria, serving the Nadezhda residential district.
-
D.
Kachinskaya station
Kachinskaya station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
-
E.
Zhdanovskaya station
Zhdanovskaya station is a former terminus station on the Moscow Metro’s Taganskaya–Zhdanovskaya line, historically serving as an endpoint for trains on that route.
- 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_69d886c9c9d481909afe222093641cae |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d0a6f628819080db47285954729a |
completed | April 18, 2026, 6:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a011b3f751c81908906ec969bef55c5 |
completed | May 10, 2026, 11:56 p.m. |
| NEDg | Description generation | batch_6a011bf2d25c8190b512de2928550283 |
completed | May 10, 2026, 11:59 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a011c63308481908b32716eb913b9bd |
completed | May 11, 2026, 12:01 a.m. |
Created at: April 10, 2026, 5:31 a.m.