Triple
T15866372
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vergiate |
E384722
|
entity |
| Predicate | distanceToVarese |
P120820
|
FINISHED |
| Object | approximately 20 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 20 km | Statement: [Vergiate, distanceToVarese, approximately 20 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToVarese Context triple: [Vergiate, distanceToVarese, approximately 20 km]
-
A.
distanceFromPavia
Indicates the spatial distance between a given entity or location and the city of Pavia.
-
B.
distanceFromMilan
Indicates the spatial distance between a given entity and the city of Milan.
-
C.
distanceToSavona_km
Indicates the physical distance, measured in kilometers, between a given entity’s location and the city of Savona.
-
D.
distanceToVenice_km
Indicates the physical distance, measured in kilometers, between a given place and the city of Venice.
-
E.
distanceToLecco
Indicates a relationship where one entity has a measurable distance or spatial separation to the location Lecco.
- F. None of above. chosen
Provenance (4 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_69d86da4e86481909f1325fdc971b5ec |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e174de2cd48190ab18e48c9f051a2a |
completed | April 16, 2026, 11:46 p.m. |
| PD | Predicate disambiguation | batch_69e142b976c081908d3ba3e705419f3a |
completed | April 16, 2026, 8:12 p.m. |
| PDg | Predicate description generation | batch_69e174da2c2c819099ec46616798245a |
completed | April 16, 2026, 11:46 p.m. |
Created at: April 10, 2026, 4:50 a.m.