Triple
T26550139
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Camisano Vicentino |
E671655
|
entity |
| Predicate | roadDistanceToPadua |
P32153
|
FINISHED |
| Object | approximately 25–30 km |
—
|
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 25–30 km | Statement: [Camisano Vicentino, roadDistanceToPadua, approximately 25–30 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roadDistanceToPadua Context triple: [Camisano Vicentino, roadDistanceToPadua, approximately 25–30 km]
-
A.
distanceToPadua
chosen
Indicates the measured distance between a given entity’s location and the city of Padua.
-
B.
distanceFromPavia
Indicates the spatial distance between a given entity or location and the city of Pavia.
-
C.
distanceFromPerugia
Indicates the spatial distance between a given entity and the location of Perugia.
-
D.
distanceToBologna
Indicates the spatial distance between a given entity and the city of Bologna.
-
E.
distanceToBrindisi
Indicates the measured or specified distance between a given entity or location and the city of Brindisi.
- 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_69eeb32163f08190af5f81282738e27a |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f614391e4c81908b14843830640ad1 |
completed | May 2, 2026, 3:11 p.m. |
| PD | Predicate disambiguation | batch_69f602d7b1b0819095ddd3b5169f8ce2 |
completed | May 2, 2026, 1:57 p.m. |
Created at: April 27, 2026, 1:46 a.m.