Triple
T12398070
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Малая Нева |
E296172
|
entity |
| Predicate | имеетНабережные |
P87034
|
FINISHED |
| Object | набережные Васильевского острова |
—
|
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: набережные Васильевского острова | Statement: [Малая Нева, имеетНабережные, набережные Васильевского острова]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: имеетНабережные Context triple: [Малая Нева, имеетНабережные, набережные Васильевского острова]
-
A.
cityDistrictOnShore
Indicates that a city district is located along or directly adjacent to the shore of a body of water.
-
B.
hasWaterfrontAccessTo
chosen
Indicates that one entity is directly adjacent to and can physically access a particular body of water, such as a lake, river, or ocean.
-
C.
northernShore
Indicates that one entity is located on the northern shore or northern side of another entity, typically a body of water or coastline.
-
D.
hasBeachNearby
Indicates that one location is situated close enough to another location to have convenient access to a beach.
-
E.
hasHighwayAlongShore
Indicates that a highway runs adjacent to or closely follows the shoreline of a body of water.
- 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_69d6ad9f464c81909db36d7e96e34b9e |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d93fd448f08190af425a569d7ed158 |
completed | April 10, 2026, 6:22 p.m. |
| PD | Predicate disambiguation | batch_69d93ed4cea08190ad374d3f6a798053 |
completed | April 10, 2026, 6:17 p.m. |
Created at: April 8, 2026, 9:54 p.m.