Triple
T36978104
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | O*NET |
E914750
|
entity |
| Predicate | hasModelElement |
P197425
|
FINISHED |
| Object | worker characteristics |
—
|
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: worker characteristics | Statement: [O*NET, hasModelElement, worker characteristics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasModelElement Context triple: [O*NET, hasModelElement, worker characteristics]
-
A.
hasModelIn
Indicates that an entity is represented or instantiated as a model within a specified context, system, or container.
-
B.
hasModelLine
Indicates that an item, product, or entity belongs to or is associated with a particular model line or series.
-
C.
hasComponentModel
Indicates that an entity includes or is associated with a specific component model as part of its structure or configuration.
-
D.
hasModels
chosen
Indicates that an entity possesses, defines, or is associated with one or more models (such as conceptual, mathematical, or data models).
-
E.
hasModelType
Indicates that an entity is associated with or classified under a specific model type.
- 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_69f76e8d13b4819089af24a47ce092fc |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69ff7fc835f08190afd1f8129b7a62a2 |
completed | May 9, 2026, 6:41 p.m. |
| PD | Predicate disambiguation | batch_69ff7f2e99ac8190ba372a1358a05a30 |
completed | May 9, 2026, 6:38 p.m. |
Created at: May 3, 2026, 4:14 p.m.