Triple
T15401346
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Goulburn Court House |
E368322
|
entity |
| Predicate | hasSymmetricalFacade |
P50368
|
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: [Goulburn Court House, hasSymmetricalFacade, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSymmetricalFacade Context triple: [Goulburn Court House, hasSymmetricalFacade, yes]
-
A.
hasFacadeSystem
Indicates that one entity possesses or is equipped with a particular façade system as part of its structure or design.
-
B.
isSymmetrical
chosen
Indicates that an object, pattern, or configuration remains unchanged or mirrored when transformed by a symmetry operation such as reflection, rotation, or inversion.
-
C.
hasSymmetryType
Indicates that one entity possesses a specific kind or pattern of symmetry characterized or classified by the other entity.
-
D.
isSymmetric
Indicates that a relationship holds in both directions between two entities, so if it applies from A to B, it also applies from B to A.
-
E.
isSymmetricAbout
Indicates that one entity is a mirror image of another with respect to a specified axis, point, or plane of symmetry.
- 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_69d85a16c68c819099c1b547fbc87b32 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e8ea0ac8190a5c68b1951ad3db1 |
completed | April 16, 2026, 1:42 a.m. |
| PD | Predicate disambiguation | batch_69ded27b8cac8190bfa77698d53c5d1c |
completed | April 14, 2026, 11:49 p.m. |
Created at: April 10, 2026, 3:19 a.m.