Triple
T15027396
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arona |
E378251
|
entity |
| Predicate | hasRegionCapitalDistance |
P10889
|
FINISHED |
| Object | about 70 km northwest of Milan |
—
|
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: about 70 km northwest of Milan | Statement: [Arona, hasRegionCapitalDistance, about 70 km northwest of Milan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRegionCapitalDistance Context triple: [Arona, hasRegionCapitalDistance, about 70 km northwest of Milan]
-
A.
distanceFromCapital
chosen
Indicates the measured distance between a given location and the capital city of its corresponding region or country.
-
B.
regionCapitalDistanceRelation
Indicates a relationship specifying the distance between a region and its capital.
-
C.
regionCapitalNearby
Indicates that a capital city of a region is located close to the referenced place or entity.
-
D.
stateCapitalProximity
Indicates the spatial closeness or distance between a state’s capital city and another specified location.
-
E.
hasCountyCapitalDistance
Indicates a distance relationship specifying how far a county is from its capital.
- 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_69d85cd46b2c819090d054c27787f677 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded7dfcb508190aec8cd667e27a8ea |
completed | April 15, 2026, 12:12 a.m. |
| PD | Predicate disambiguation | batch_69de9a67cbc481909c19c2de57de4eb7 |
completed | April 14, 2026, 7:50 p.m. |
Created at: April 10, 2026, 2:58 a.m.