Triple
T32241900
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sakiai |
E823636
|
entity |
| Predicate | hasBorderProximityCharacteristic |
P131063
|
FINISHED |
| Object | near Russian border |
—
|
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: near Russian border | Statement: [Sakiai, hasBorderProximityCharacteristic, near Russian border]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBorderProximityCharacteristic Context triple: [Sakiai, hasBorderProximityCharacteristic, near Russian border]
-
A.
hasBorderAreaCharacteristics
Indicates that something possesses features or qualities typical of a border area between regions or territories.
-
B.
hasBorderLengthCharacteristic
Indicates that a border is associated with a specific length-related property or characteristic.
-
C.
hasProximitySensor
Indicates that an entity is equipped with a sensor capable of detecting nearby objects or measuring its distance to them.
-
D.
hasNearbyBoundary
chosen
Indicates that one entity’s boundary lies close to, but does not necessarily touch or coincide with, the boundary of another entity.
-
E.
nearStateBorderWith
Indicates that one entity is located close to the state border shared with another specified state or region.
- 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_69f3490cdda88190a9d61e11252a771f |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fd3a69f1e08190a11aed015bff0858 |
completed | May 8, 2026, 1:20 a.m. |
| PD | Predicate disambiguation | batch_69fd39124180819080ca7911d3515d6d |
completed | May 8, 2026, 1:14 a.m. |
Created at: May 1, 2026, 12:40 a.m.