Triple
T30166492
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Вознесенский проспект |
E766805
|
entity |
| Predicate | значениеДляГорода |
P132799
|
FINISHED |
| Object | формирует исторический облик центра |
—
|
LITERAL 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: формирует исторический облик центра | Statement: [Вознесенский проспект, значениеДляГорода, формирует исторический облик центра]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: значениеДляГорода Context triple: [Вознесенский проспект, значениеДляГорода, формирует исторический облик центра]
-
A.
goalOfCity
Indicates that a particular objective, purpose, or target is associated with or pursued by a given city.
-
B.
cityService
Indicates that a service is provided by, operates within, or is administered by a particular city.
-
C.
city2
Indicates a relationship where one entity is identified as a city associated with, located in, or otherwise linked to another entity.
-
D.
cityWideSignificance
chosen
Indicates that something has importance, impact, or relevance at the scale of an entire city rather than just a local or individual level.
-
E.
cityFunction
Indicates the primary role, purpose, or functional classification associated with a city (e.g., administrative, commercial, industrial, cultural).
- F. None of above.
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_69f2247a968881909d79c18f2bfcb275 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f67f073dbc8190a42f4c71ad2f7de3 |
completed | May 2, 2026, 10:47 p.m. |
| PD | Predicate disambiguation | batch_69f673c7a4588190837854f3ef61e6bf |
completed | May 2, 2026, 9:59 p.m. |
Created at: April 29, 2026, 7:23 p.m.