Triple
T265026
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | .NET Framework |
E5703
|
entity |
| Predicate | targetApplicationType |
P4243
|
FINISHED |
| Object | desktop applications |
—
|
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: desktop applications | Statement: [.NET Framework, targetApplicationType, desktop applications]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetApplicationType Context triple: [.NET Framework, targetApplicationType, desktop applications]
-
A.
appliesTo
Indicates that something is relevant, valid, or has effect in relation to a particular entity, case, or context.
-
B.
launcherType
Indicates the specific kind or category of launcher associated with or used in relation to an entity.
-
C.
supportsProjectType
chosen
Indicates that one entity is capable of handling, accommodating, or being compatible with a specified type of project.
-
D.
hasPlatformType
Indicates that an entity is associated with or characterized by a specific type or category of platform.
-
E.
usageType
Indicates the specific manner, purpose, or context in which something is used or intended to be used.
- 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_69a2587daeb081909591b9d30f80a271 |
completed | Feb. 28, 2026, 2:52 a.m. |
| NER | Named-entity recognition | batch_69a25d8f9bbc8190a13841e4de093a66 |
completed | Feb. 28, 2026, 3:14 a.m. |
| PD | Predicate disambiguation | batch_69a25b6e07748190834022a65ba6d803 |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:56 a.m.