Triple
T16013687
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ploshchad Gagarina station |
E388405
|
entity |
| Predicate | hasNativeName |
P1435
|
FINISHED |
| Object | станция «Площадь Гагарина» |
E242485
|
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: станция «Площадь Гагарина» | Statement: [Ploshchad Gagarina station, hasNativeName, станция «Площадь Гагарина»]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: станция «Площадь Гагарина» Context triple: [Ploshchad Gagarina station, hasNativeName, станция «Площадь Гагарина»]
-
A.
Gagarina station
chosen
Gagarina station is a stop on the Volgograd Metrotram system in Volgograd, Russia, named in honor of cosmonaut Yuri Gagarin.
-
B.
Ploshchad Vozrozhdeniya station
Ploshchad Vozrozhdeniya station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
-
C.
Lomonosovskaya station
Lomonosovskaya station is a metro station on Saint Petersburg’s Line 3 (Nevsko–Vasileostrovskaya Line), serving the southeastern part of the city near the Neva River.
-
D.
Ploshchad Truda station
Ploshchad Truda station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
-
E.
Troparyovo station
Troparyovo station is a Moscow Metro station serving the southwestern part of the city on one of its main radial lines.
- 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_69d86dabcb7c8190b6a39d6831d2fa1b |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e18292b79881908efac869603c4029 |
completed | April 17, 2026, 12:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffcf267a9c81908f1fa1ad117c5e2c |
completed | May 10, 2026, 12:19 a.m. |
Created at: April 10, 2026, 4:55 a.m.