Triple
T18862448
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pontebbana railway line |
E461346
|
entity |
| Predicate | hasBorderTerminusWith |
P27716
|
FINISHED |
| Object | Austrian railway network |
—
|
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: Austrian railway network | Statement: [Pontebbana railway line, hasBorderTerminusWith, Austrian railway network]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBorderTerminusWith Context triple: [Pontebbana railway line, hasBorderTerminusWith, Austrian railway network]
-
A.
hasBorderTerminus
chosen
Indicates that one entity serves as the endpoint or terminal location of another entity’s border or boundary.
-
B.
hasBorderTerminusCountry
Indicates that a country serves as the endpoint or boundary limit of a border segment associated with another entity.
-
C.
hasBorderConnection
Indicates that two regions or entities share a common boundary or are directly connected along a border.
-
D.
hasBorderRelation
Indicates that one entity shares a boundary or border with another entity.
-
E.
hasBorderThrough
Indicates that a border between two regions or entities passes through or along a specified intermediate area, feature, or object.
- 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_69d8dcfb7b9c8190854e7b171b98ea2e |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c06184d88190bd05413a07a8c9ce |
completed | April 20, 2026, 5:57 a.m. |
| PD | Predicate disambiguation | batch_69e48d2166b88190add38de96cedc65c |
completed | April 19, 2026, 8:06 a.m. |
Created at: April 10, 2026, 11:57 a.m.