Triple
T29835273
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mulazzano |
E757637
|
entity |
| Predicate | isInCommutingDistanceOf |
P61362
|
FINISHED |
| Object | Milan |
—
|
NE NERFINISHED |
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: Milan | Statement: [Mulazzano, isInCommutingDistanceOf, Milan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isInCommutingDistanceOf Context triple: [Mulazzano, isInCommutingDistanceOf, Milan]
-
A.
hasTransportationProximityTo
Indicates that one entity is located near or conveniently accessible to another entity in terms of transportation options or routes.
-
B.
hasApproximateDrivingDistanceFrom
Indicates that one entity is located at an estimated or approximate driving distance from another entity, typically measured along road routes rather than as a precise or exact value.
-
C.
isFartherFromCityCenterThan
Indicates that one location is at a greater distance from the city center than another location.
-
D.
nearbyTo
chosen
Indicates that one entity is located close in distance or position to another entity.
-
E.
commutesBetween
Indicates a regular pattern of travel back and forth between two locations, typically for work, study, or routine activities.
- 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_69f224593f6c81908785a560fe659f58 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f67605e9548190855ca2d77608b4dc |
completed | May 2, 2026, 10:09 p.m. |
| PD | Predicate disambiguation | batch_69f673c4abec8190bc2379e66f4af0a9 |
completed | May 2, 2026, 9:59 p.m. |
Created at: April 29, 2026, 5:36 p.m.