Triple
T19436762
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rational Software |
E486242
|
entity |
| Predicate | usedUML |
P35898
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Rational Software, usedUML, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedUML Context triple: [Rational Software, usedUML, true]
-
A.
usesClass
Indicates that one entity makes use of, depends on, or is implemented using a particular class in its structure or behavior.
-
B.
usedByClass
Indicates that something (such as a resource, method, or component) is utilized or depended upon by a particular class.
-
C.
usedToClassify
Indicates that one entity serves as a criterion or basis for categorizing or grouping another entity.
-
D.
usedToModel
chosen
Indicates that one entity serves as a model or representation for another entity, typically for purposes of analysis, simulation, or understanding.
-
E.
usedProgramModel
Indicates that an entity employed a specific program model as the basis or framework for its activities or operations.
- 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_69d8e8d7ad488190a3373045029b0f3b |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e633618c2881908f3d2a9cabb02289 |
completed | April 20, 2026, 2:08 p.m. |
| PD | Predicate disambiguation | batch_69e4fd6e806081909053f325ba01ab6b |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 1:38 p.m.