Triple
T16596907
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Strade Bianche |
E403230
|
entity |
| Predicate | gravelSectorTotalDistanceApproxKm |
P112593
|
FINISHED |
| Object | 60 |
—
|
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: 60 | Statement: [Strade Bianche, gravelSectorTotalDistanceApproxKm, 60]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: gravelSectorTotalDistanceApproxKm Context triple: [Strade Bianche, gravelSectorTotalDistanceApproxKm, 60]
-
A.
trailDistanceApprox
Indicates that the distance along a trail between two locations is approximately a specified value, allowing for some margin of error.
-
B.
trailDistanceContext
Indicates the contextual distance or separation between entities along a trail, path, or route.
-
C.
trackLengthApproxKm
Indicates that one entity has an approximate track length, measured in kilometers, associated with it.
-
D.
hasCyclingDistance
Indicates that there is a specified distance associated with traveling between entities by cycling.
-
E.
distanceOfCourse
chosen
Indicates the length or total distance covered by a course or route.
- 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_69d883880d0c81908b5fcd454e767b60 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e35d723c508190b5afbda5eec5abea |
completed | April 18, 2026, 10:31 a.m. |
| PD | Predicate disambiguation | batch_69e296a7d9d0819088555bca6c936e79 |
completed | April 17, 2026, 8:23 p.m. |
Created at: April 10, 2026, 5:16 a.m.