Triple
T15384810
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red Shell |
E367889
|
entity |
| Predicate | has3DModel |
P48562
|
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: [Red Shell, has3DModel, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: has3DModel Context triple: [Red Shell, has3DModel, yes]
-
A.
has3DModels
chosen
Indicates that an entity is associated with one or more three-dimensional (3D) digital models representing it.
-
B.
has3DVersion
Indicates that an entity has a corresponding three-dimensional (3D) version or representation.
-
C.
has3DGraphics
Indicates that something includes or supports three-dimensional graphical representation or rendering.
-
D.
hasRealModel
Indicates that an abstract, theoretical, or simplified entity is associated with a corresponding concrete or physically instantiated model in the real world.
-
E.
hadModel
Indicates that an entity possessed, used, or was associated with a particular model (e.g., a product, design, or version) at some point in time.
- 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_69d85a1551a08190ba2caea7cd51c639 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e7397188190bde42b897ab4b5b4 |
completed | April 16, 2026, 1:42 a.m. |
| PD | Predicate disambiguation | batch_69ded27742a881909cd73cc5c7d062fd |
completed | April 14, 2026, 11:49 p.m. |
Created at: April 10, 2026, 3:19 a.m.