Triple
T19332659
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Южный федеральный округ |
E483534
|
entity |
| Predicate | bordersWithSea |
P212
|
FINISHED |
| Object | Чёрное море |
—
|
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: Чёрное море | Statement: [Южный федеральный округ, bordersWithSea, Чёрное море]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bordersWithSea Context triple: [Южный федеральный округ, bordersWithSea, Чёрное море]
-
A.
hasLandBorderWithSea
Indicates that an entity’s land area directly borders or touches a sea along its coastline.
-
B.
bordersStateAcrossSea
Indicates that one state is separated from another by a sea but still directly borders it across that body of water.
-
C.
isPartOfCoastOf
Indicates that one entity forms a segment or component of the coastline belonging to another entity.
-
D.
hasCoastlineOn
chosen
Indicates that one entity’s coastline borders or is directly adjacent to a specified body of water.
-
E.
hasCountryCoastline
Indicates that a country possesses a coastline along a sea or ocean.
- 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_69d8e8d13e3c81909d91d1d5ec37c095 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e61642f49c81909226cfd701f7c139 |
completed | April 20, 2026, 12:04 p.m. |
| PD | Predicate disambiguation | batch_69e4dd12303c8190a2027c062b2dff40 |
completed | April 19, 2026, 1:48 p.m. |
Created at: April 10, 2026, 1:33 p.m.