Triple
T14855950
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wineglass Bay Lookout |
E349349
|
entity |
| Predicate | hasTrackSurface |
P115885
|
FINISHED |
| Object | formed track |
—
|
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: formed track | Statement: [Wineglass Bay Lookout, hasTrackSurface, formed track]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTrackSurface Context triple: [Wineglass Bay Lookout, hasTrackSurface, formed track]
-
A.
hasTrack
Indicates that one entity possesses, includes, or is associated with a specific track (such as a path, course, or recorded item).
-
B.
hasPrimarySurface
Indicates that one entity serves as the main or principal surface associated with another entity.
-
C.
hasTrackSection
Indicates that an entity includes, is composed of, or is associated with a specific section or segment of a track.
-
D.
hasSurfaceSections
Indicates that an entity is composed of or divided into distinct sections or parts of its surface.
-
E.
hasSurfaceAccuracy
Indicates that one entity possesses a specified degree or measure of accuracy related to its surface characteristics or representation.
- 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_69d822ed7e1881909b90fca143ad7e34 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded44458ec8190be295a95f5daab14 |
completed | April 14, 2026, 11:56 p.m. |
| PD | Predicate disambiguation | batch_69de8c1798c08190b433e9ad21e41a42 |
completed | April 14, 2026, 6:48 p.m. |
| PDg | Predicate description generation | batch_69de8f4b67cc8190b84b59fcec5cf579 |
completed | April 14, 2026, 7:02 p.m. |
Created at: April 10, 2026, 1:54 a.m.