Triple
T8291216
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Ainslie Lookout |
E193899
|
entity |
| Predicate | hasPanoramicViewOver |
P29603
|
FINISHED |
| Object | Canberra and its landmarks |
—
|
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: Canberra and its landmarks | Statement: [Mount Ainslie Lookout, hasPanoramicViewOver, Canberra and its landmarks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPanoramicViewOver Context triple: [Mount Ainslie Lookout, hasPanoramicViewOver, Canberra and its landmarks]
-
A.
hasPanoramicView
chosen
Indicates that something offers a wide, unobstructed view over a broad surrounding area.
-
B.
hasSummitPanorama
Indicates that a summit location offers a panoramic view or image captured from its highest point.
-
C.
hasViewThrough
Indicates that one entity can be seen or visually perceived through another entity acting as an intermediate medium or opening.
-
D.
hasFieldOfView
Indicates that one entity possesses a visual coverage area within which it can perceive or detect other entities or regions.
-
E.
hasViewingPlatform
Indicates that an entity includes or is equipped with a designated platform or area intended for viewing or observing something.
- 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_69ca82e32db481908b72f3804fa71152 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7c9b65e0819083ddc82fb7c4a5f3 |
completed | March 31, 2026, 7:49 a.m. |
| PD | Predicate disambiguation | batch_69cb70b5b5348190b296e0ecec95de60 |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 5:52 p.m.