Triple
T3931826
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Passo dello Stelvio |
E90810
|
entity |
| Predicate | hasHairpinBends |
P52595
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Passo dello Stelvio, hasHairpinBends, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHairpinBends Context triple: [Passo dello Stelvio, hasHairpinBends, yes]
-
A.
hasNumberOfHairpinTurns
Indicates the quantity of hairpin turns associated with an entity, such as a road or path.
-
B.
hasNumberOfArches
Indicates the relationship specifying how many arches are present in or associated with a given entity.
-
C.
bendAngle
Indicates the degree to which one part is bent relative to another, typically measured as the angle formed at their joint or intersection.
-
D.
hasStraightLines
Indicates that the related entity possesses or is characterized by straight, non-curved lines.
-
E.
hasBridges
Indicates that one entity possesses, contains, or is characterized by one or more bridges connecting locations or components.
- 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_69aed95f26e0819094b0e71974543a19 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeeda98058819094dd6ab223670860 |
completed | March 9, 2026, 3:56 p.m. |
| PD | Predicate disambiguation | batch_69aee7625ad4819097e4e8a168c19274 |
completed | March 9, 2026, 3:29 p.m. |
| PDg | Predicate description generation | batch_69aeed3260cc8190bf294bdab507b1f9 |
completed | March 9, 2026, 3:54 p.m. |
Created at: March 9, 2026, 3:23 p.m.