Triple
T14758333
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pushkinsky District |
E346788
|
entity |
| Predicate | hasPark |
P105
|
FINISHED |
| Object | Fermsky Park |
E954386
|
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: Fermsky Park | Statement: [Pushkinsky District, hasPark, Fermsky Park]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fermsky Park Context triple: [Pushkinsky District, hasPark, Fermsky Park]
-
A.
Fermsky Park
chosen
Fermsky Park is a public green space in the Pushkinsky District of Saint Petersburg, Russia, offering residents and visitors areas for recreation and outdoor leisure.
-
B.
Belinsky Park
Belinsky Park is a notable public park and recreational green space in the city of Penza, Russia.
-
C.
Petrovsky Park
Petrovsky Park is a historic green space in Moscow known for its 19th-century Petrovsky Palace and proximity to major sports and cultural venues.
-
D.
Vlasis Park
Vlasis Park is a popular community park in Ballwin, Missouri, featuring recreational facilities, open green spaces, and areas for local events and outdoor activities.
-
E.
Bitsevsky Park
Bitsevsky Park is a station on the Moscow Metro serving the area near the large Bitsevskiy forest park in southern Moscow.
- 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_69d822e8896c819091169882f9b20486 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec7f0f5a48190af008352c26574d7 |
completed | April 14, 2026, 11:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe72a347808190a72dfd3a1b776982 |
completed | May 8, 2026, 11:32 p.m. |
Created at: April 10, 2026, 1:30 a.m.