Triple
T27911659
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Blaha |
E705943
|
entity |
| Predicate | usesModelingLanguage |
P172124
|
FINISHED |
| Object | UML |
—
|
NE NERFINISHED |
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: UML | Statement: [Michael Blaha, usesModelingLanguage, UML]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesModelingLanguage Context triple: [Michael Blaha, usesModelingLanguage, UML]
-
A.
supportsModelingOf
Indicates that one entity provides the capability or functionality needed to represent, simulate, or model another entity or process.
-
B.
requiresModelingOf
Indicates that one entity depends on another entity being represented or simulated in a model in order for it to be properly defined, analyzed, or executed.
-
C.
usesModelsType
Indicates that one entity employs or relies on a specific type or category of models in its operation or behavior.
-
D.
usedProgramModel
Indicates that an entity employed a specific program model as the basis or framework for its activities or operations.
-
E.
usesDesignModel
Indicates that one entity applies or relies on a particular design model in performing its function or defining its structure.
- 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_69ef96b5aad08190be36a277c31e7004 |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69f6a9603b208190b3533ea2b441514c |
completed | May 3, 2026, 1:48 a.m. |
| PD | Predicate disambiguation | batch_69f6a751d5e48190a77dcecbe7ef9f0b |
completed | May 3, 2026, 1:39 a.m. |
| PDg | Predicate description generation | batch_69f6a8de0b948190ae333e9cd99cbf6c |
completed | May 3, 2026, 1:46 a.m. |
Created at: April 27, 2026, 6:50 p.m.