Triple
T20368550
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bulgarian rail network |
E496982
|
entity |
| Predicate | connectsBorderCrossings |
P64605
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Bulgarian rail network, connectsBorderCrossings, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: connectsBorderCrossings Context triple: [Bulgarian rail network, connectsBorderCrossings, yes]
-
A.
usesBorderCrossing
Indicates that one entity makes use of a specific border crossing point to pass from one jurisdiction or territory to another.
-
B.
hasBorderCrossing
Indicates that there exists a point or facility where movement or transit is possible between the boundaries of two adjacent regions or jurisdictions.
-
C.
nearBorderCrossing
Indicates that an entity is located close to a border crossing point between two regions or countries.
-
D.
hasRailBorderCrossing
chosen
Indicates that two places are connected by at least one official border crossing that is served by rail transport.
-
E.
borderTownAcrossBorder
Indicates that a town lies on one side of a border directly opposite or adjacent to a town on the other side of that border.
- 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_69e0b4a4f9b081908a5a021919c21ccb |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e678734b188190bb2c5863023f9f8c |
completed | April 20, 2026, 7:03 p.m. |
| PD | Predicate disambiguation | batch_69e57648be3c81908256838228cabf5c |
completed | April 20, 2026, 12:41 a.m. |
Created at: April 16, 2026, 11:26 a.m.