Triple
T30419833
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | правый берег Невы |
E773867
|
entity |
| Predicate | имеетТипЗастройки |
P122880
|
FINISHED |
| Object | городская застройка |
—
|
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: городская застройка | Statement: [правый берег Невы, имеетТипЗастройки, городская застройка]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: имеетТипЗастройки Context triple: [правый берег Невы, имеетТипЗастройки, городская застройка]
-
A.
типСтроения
Indicates the specific kind or category of building or structure associated with an entity.
-
B.
architectureType
Indicates the specific style or category of architecture that characterizes or defines an entity.
-
C.
domicileType
Indicates the category or kind of residence or dwelling associated with an entity.
-
D.
hasResidentialBuildingsType
chosen
Indicates that an entity is associated with a specific type or category of residential buildings.
-
E.
typeOfHouse
Indicates the specific category or kind of house associated with an entity (e.g., apartment, detached house, townhouse).
- 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_69f22491ba248190b9a4776ca8e42d02 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f68a16debc8190a12f5f65ced055d7 |
completed | May 2, 2026, 11:34 p.m. |
| PD | Predicate disambiguation | batch_69f6860def1c81909d79e1f088c4b5e5 |
completed | May 2, 2026, 11:17 p.m. |
Created at: April 29, 2026, 8:05 p.m.