Triple
T8993256
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DOS/VS |
E214839
|
entity |
| Predicate | jobControlLanguage |
P83528
|
FINISHED |
| Object | DOS JCL |
—
|
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: DOS JCL | Statement: [DOS/VS, jobControlLanguage, DOS JCL]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: jobControlLanguage Context triple: [DOS/VS, jobControlLanguage, DOS JCL]
-
A.
supportsJobControlLanguage
chosen
Indicates that one entity provides compatibility with or the ability to execute and manage operations defined in a job control language for another entity.
-
B.
jobInput
Indicates that one entity serves as an input or required resource for performing or executing a particular job or task involving another entity.
-
C.
controlStructure
Indicates a relationship where one entity governs, regulates, or directs the behavior, operation, or flow of another entity or process.
-
D.
controlInnovation
Indicates that one entity directs, regulates, or significantly influences the innovation activities or outcomes of another entity.
-
E.
executionModel
Indicates how a process, task, or operation is carried out or implemented, specifying the underlying method, strategy, or mechanism of its execution.
- 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_69ca83a05c608190bdfdbdb25e994b39 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6876583081909d936dc3c3152587 |
completed | April 1, 2026, 12:36 a.m. |
| PD | Predicate disambiguation | batch_69cc5edba0f88190b97401636a076d7a |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 7:04 p.m.