Triple
T9100467
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Park Kultury station |
E218137
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Krymsky Val |
E778160
|
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: Krymsky Val | Statement: [Park Kultury station, near, Krymsky Val]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Krymsky Val Context triple: [Park Kultury station, near, Krymsky Val]
-
A.
Krymsky Val
chosen
Krymsky Val is a notable street in central Moscow, Russia, known for its proximity to Gorky Park and several major cultural institutions.
-
B.
Khreshchatyi Yar
Khreshchatyi Yar is the historic ravine area in central Kyiv whose name gave rise to the city’s main thoroughfare, Khreshchatyk Street.
-
C.
Vyshny Volochyok
Vyshny Volochyok is a historic town in Tver Oblast, Russia, known as a former key transport hub on the waterway between Moscow and Saint Petersburg.
-
D.
Kakhovskaya
Kakhovskaya is a Moscow Metro station that serves as part of the city’s Big Circle Line.
-
E.
Medveditsa
Medveditsa is a river in southwestern Russia that flows through the Volgograd and Saratov regions before joining the Don River.
- 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_69ca83d9844081908e561e367fda6d45 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc9711babc8190a336812dd08d9c73 |
completed | April 1, 2026, 3:54 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d030201a048190a3a1166d23c5ae67 |
completed | April 3, 2026, 9:24 p.m. |
Created at: March 30, 2026, 7:15 p.m.