Triple
T9566694
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Standard ML |
E230804
|
entity |
| Predicate | hasModuleComponent |
P12988
|
FINISHED |
| Object | signatures |
—
|
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: signatures | Statement: [Standard ML, hasModuleComponent, signatures]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasModuleComponent Context triple: [Standard ML, hasModuleComponent, signatures]
-
A.
hasModuleConstruct
chosen
Indicates that an entity includes, defines, or is composed of a specific module as one of its structural or functional components.
-
B.
hasComponentModel
Indicates that an entity includes or is associated with a specific component model as part of its structure or configuration.
-
C.
hasServerComponent
Indicates that an entity includes, depends on, or is associated with a particular server-side component.
-
D.
hasSubcomponent
Indicates that one entity is a constituent part or component of another, larger entity.
-
E.
hasComponentProgram
Indicates that one program includes or is composed of another program as a component or sub-program.
- 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_69ca847f22188190a56e4a97625bef22 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd996df4f08190b19bbaefb10a9789 |
completed | April 1, 2026, 10:17 p.m. |
| PD | Predicate disambiguation | batch_69ccd59b960c8190966a8870a2426bd5 |
completed | April 1, 2026, 8:21 a.m. |
Created at: March 30, 2026, 8:04 p.m.