Triple
T38073599
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berkeley School of cultural geography |
E950649
|
entity |
| Predicate | viewOnLandscape |
P93634
|
FINISHED |
| Object | landscape as a record of human activity |
—
|
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: landscape as a record of human activity | Statement: [Berkeley School of cultural geography, viewOnLandscape, landscape as a record of human activity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: viewOnLandscape Context triple: [Berkeley School of cultural geography, viewOnLandscape, landscape as a record of human activity]
-
A.
landscapeView
Indicates that one entity provides or features a scenic or panoramic view of a landscape from the perspective of another entity.
-
B.
viewIs
chosen
Indicates that one entity is a visual representation or perspective of another entity.
-
C.
viewOver
Indicates that one entity has a visual perspective overlooking or facing another entity, typically providing a vantage point onto it.
-
D.
viewOnSidewaysMovements
Indicates that an entity observes or evaluates movements occurring in a sideways or lateral direction.
-
E.
viewOnImages
Indicates that one entity views or displays another entity specifically in the form of images.
- 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_69f76f02a6c48190a94f3c0b3ee90cf2 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fd5bf69acc819092a01e4259785dc3 |
completed | May 8, 2026, 3:43 a.m. |
| PD | Predicate disambiguation | batch_69fd59b3f4ac8190a7f9dd3142da6e09 |
completed | May 8, 2026, 3:34 a.m. |
Created at: May 3, 2026, 4:21 p.m.