Triple
T25372579
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Styx protocol |
E632967
|
entity |
| Predicate | interfaceModel |
P105324
|
FINISHED |
| Object | file-oriented interface |
—
|
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: file-oriented interface | Statement: [Styx protocol, interfaceModel, file-oriented interface]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: interfaceModel Context triple: [Styx protocol, interfaceModel, file-oriented interface]
-
A.
modelIn
Indicates that one entity serves as a representation or simulation of another entity.
-
B.
namespaceModel
Indicates a relationship where a model is defined within, or associated with, a particular namespace or logical grouping.
-
C.
typicalInterface
chosen
Indicates that one entity serves as the standard or commonly used interface through which another entity is accessed or interacted with.
-
D.
interfaceLocation
Indicates the spatial or logical position where two systems, components, or entities meet and interact.
-
E.
modeledWith
Indicates that something is represented, simulated, or described using a particular model, method, or modeling technique.
- 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_69e75a90c0dc819092f928b6ea0ecc72 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f627aedf548190bc9f53c8a2d67b50 |
completed | May 2, 2026, 4:34 p.m. |
| PD | Predicate disambiguation | batch_69f623a4e1048190bbb8dd1253fdcee9 |
completed | May 2, 2026, 4:17 p.m. |
Created at: April 21, 2026, 1:38 p.m.