Triple
T1368186
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adobe Flash |
E30049
|
entity |
| Predicate | supportedContentType |
P24486
|
FINISHED |
| Object | vector graphics |
—
|
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: vector graphics | Statement: [Adobe Flash, supportedContentType, vector graphics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportedContentType Context triple: [Adobe Flash, supportedContentType, vector graphics]
-
A.
supportsType
chosen
Indicates that one entity is capable of handling, accepting, or being compatible with a specified type.
-
B.
offersContentType
Indicates that one entity provides or makes available content of a specified type to another entity or context.
-
C.
supportsTargetType
Indicates that one entity is capable of operating with, handling, or being compatible with a specified target type.
-
D.
hasContentType
Indicates that an entity is associated with or classified by a specific type of content.
-
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_69a498f912008190a376a98b207b2071 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c2d497f88190993d16a208ced43d |
completed | March 1, 2026, 10:51 p.m. |
| PD | Predicate disambiguation | batch_69a4befb08b88190be966fa1aadd4bcd |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:57 p.m.