Triple
T15948424
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Petrodvortsovy District |
E386748
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Strelna |
E376482
|
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: Strelna | Statement: [Petrodvortsovy District, contains, Strelna]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Strelna Context triple: [Petrodvortsovy District, contains, Strelna]
-
A.
Strelna
chosen
Strelna is a suburban settlement near Saint Petersburg, Russia, known for its historic palaces and role as an imperial residence area.
-
B.
Strelnikov
Strelnikov is the revolutionary alias of Pasha Antipov, a radical Bolshevik leader in Boris Pasternak’s novel "Doctor Zhivago."
-
C.
Voykovskaya
Voykovskaya is a Moscow Metro station serving the Zamoskvoretskaya Line in the northern part of the city.
-
D.
Strilkove
Strilkove is a small village located on the Arabat Spit in the Kherson region of southern Ukraine, known for its coastal setting along the Sea of Azov.
-
E.
Dobryninskaya
Dobryninskaya is a Moscow Metro station on the circular Koltsevaya Line, known for its Stalinist-era architecture and central location.
- 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_69d86da882448190a82ea962fe343b79 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e156d3cc04819097367369a78d6ef2 |
completed | April 16, 2026, 9:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffb5c0c8a481908aa7a40bca15e38e |
completed | May 9, 2026, 10:31 p.m. |
Created at: April 10, 2026, 4:53 a.m.