Triple
T9100667
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Salaryevo station |
E218141
|
entity |
| Predicate | hasAdjacentStation |
P231
|
FINISHED |
| Object | Filatov Lug station |
E330061
|
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: Filatov Lug station | Statement: [Salaryevo station, hasAdjacentStation, Filatov Lug station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Filatov Lug station Context triple: [Salaryevo station, hasAdjacentStation, Filatov Lug station]
-
A.
Filatov Lug station
chosen
Filatov Lug station is a Moscow Metro station on the Sokolnicheskaya Line serving the southwestern outskirts of the city.
-
B.
Frunzenskaya station
Frunzenskaya station is a Moscow Metro station known for its deep-level construction and classic Soviet-era architectural design.
-
C.
Timiryazevskaya station
Timiryazevskaya station is a Moscow Metro station that serves as a key stop and namesake on the Serpukhovsko–Timiryazevskaya Line.
-
D.
Nadezhda station
Nadezhda station is a metro station on the Sofia Metro system in Sofia, Bulgaria, serving the Nadezhda residential district.
-
E.
Kachinskaya station
Kachinskaya station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
- 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_69d05449101481908c71475acf59b33c |
completed | April 3, 2026, 11:59 p.m. |
Created at: March 30, 2026, 7:15 p.m.