Triple
T15896791
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Como San Giovanni railway station |
E385476
|
entity |
| Predicate | distanceFromBorder |
P31353
|
FINISHED |
| Object | approximately 3 km from Swiss 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: approximately 3 km from Swiss border | Statement: [Como San Giovanni railway station, distanceFromBorder, approximately 3 km from Swiss border]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromBorder Context triple: [Como San Giovanni railway station, distanceFromBorder, approximately 3 km from Swiss border]
-
A.
distanceToBorder
chosen
Indicates the measured or estimated spatial separation between a given entity or location and the nearest relevant border or boundary.
-
B.
distanceFromCentre
Indicates the measured or specified distance of an entity from a defined central point.
-
C.
distancedFrom
Indicates that one entity is physically or metaphorically kept at a certain distance or separation from another entity.
-
D.
nearBorderDirection
Indicates that one entity is located close to a border or boundary in a specified directional orientation relative to that border.
-
E.
distanceToEnglishBorder
Indicates the spatial distance between a given location and the border of England.
- 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_69d86da5b800819083a31be937d738b0 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e17d4d08f481909f38b75e3f42d9ab |
completed | April 17, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69e142ca3b208190946c3aa4c1e6087c |
completed | April 16, 2026, 8:12 p.m. |
Created at: April 10, 2026, 4:51 a.m.