Triple
T10330189
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CityGML |
E242852
|
entity |
| Predicate | supportsGeometryType |
P24486
|
FINISHED |
| Object | surface geometry |
—
|
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: surface geometry | Statement: [CityGML, supportsGeometryType, surface geometry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsGeometryType Context triple: [CityGML, supportsGeometryType, surface geometry]
-
A.
hasGeometry
Indicates that an entity is associated with a specific geometric representation or spatial form.
-
B.
supportsType
chosen
Indicates that one entity is capable of handling, accepting, or being compatible with a specified type.
-
C.
testGeometry
Indicates that an entity is involved in evaluating, validating, or analyzing geometric properties, shapes, or spatial relationships.
-
D.
supportsTargetType
Indicates that one entity is capable of operating with, handling, or being compatible with a specified target type.
-
E.
supportsModelType
Indicates that an entity is compatible with, or can operate using, a specified model type.
- 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_69d381af787481908bc401325c760a88 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d7fb77348190ac8ff887f6f03450 |
completed | April 7, 2026, 10:10 a.m. |
| PD | Predicate disambiguation | batch_69d4d1f760e88190abea6dcc4f04f2c1 |
completed | April 7, 2026, 9:44 a.m. |
Created at: April 6, 2026, 11:52 a.m.