Triple
T35525490
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grande Grotta climbing sector |
E1026660
|
entity |
| Predicate | shade |
P109524
|
FINISHED |
| Object | offers shade during parts of the day |
—
|
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: offers shade during parts of the day | Statement: [Grande Grotta climbing sector, shade, offers shade during parts of the day]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: shade Context triple: [Grande Grotta climbing sector, shade, offers shade during parts of the day]
-
A.
shaded
Indicates that one entity partially or fully blocks light from reaching another, resulting in the latter being in shadow.
-
B.
shadeColor
Indicates that one entity has a specific shade or variation of color associated with it.
-
C.
shadeProvision
chosen
Indicates that one entity provides or creates shade or shadow for another entity.
-
D.
shadeShape
Indicates that one entity applies shading or tonal variation to define or modify the visual form of another entity’s shape.
-
E.
shadeCount
Indicates the number of distinct shades or tonal variations associated with an entity.
- 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_69f76dfe78b081908e2b14cb88dd8c00 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f79a54aa3c8190b2bb5d790b2d42d4 |
completed | May 3, 2026, 6:56 p.m. |
| PD | Predicate disambiguation | batch_69f7961970408190b669cc556e30a608 |
completed | May 3, 2026, 6:38 p.m. |
Created at: May 3, 2026, 4:04 p.m.