Triple
T2898287
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FMX |
E62593
|
entity |
| Predicate | hasComponentModel |
P43872
|
FINISHED |
| Object | visual component library |
—
|
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: visual component library | Statement: [FMX, hasComponentModel, visual component library]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasComponentModel Context triple: [FMX, hasComponentModel, visual component library]
-
A.
hasSubcomponent
Indicates that one entity is a constituent part or component of another, larger entity.
-
B.
hasComponentProgram
Indicates that one program includes or is composed of another program as a component or sub-program.
-
C.
hasComponentCurrent
Indicates that an entity currently includes or contains a specific component as part of its present composition or structure.
-
D.
hasComponentCount
Indicates that an entity is associated with a specific number of components it contains or comprises.
-
E.
hasComponentGroup
Indicates that an entity includes or is associated with a specific group of components treated as a single unit.
- 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_69ab4c3e070c8190b78d3d2c005876dd |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abe08fe3248190a6bb7de2a2c317b1 |
completed | March 7, 2026, 8:23 a.m. |
| PD | Predicate disambiguation | batch_69abdd17bcdc8190aa47274a50ba4ad4 |
completed | March 7, 2026, 8:08 a.m. |
| PDg | Predicate description generation | batch_69abde0f4c648190b9812e64f30c39da |
completed | March 7, 2026, 8:13 a.m. |
Created at: March 6, 2026, 10:10 p.m.