Triple
T29597956
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Job Entry Subsystem 3 |
E754356
|
entity |
| Predicate | languageUsedWith |
P20184
|
FINISHED |
| Object | JCL |
—
|
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: JCL | Statement: [Job Entry Subsystem 3, languageUsedWith, JCL]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageUsedWith Context triple: [Job Entry Subsystem 3, languageUsedWith, JCL]
-
A.
languageUsedAs
Indicates that one language is employed in a specific role, function, or context relative to another entity or situation.
-
B.
languagesUsed
Indicates that one entity uses, employs, or is expressed in one or more languages associated with the other entity.
-
C.
languageCategory
Indicates the classification relationship where a language is assigned to a particular linguistic or functional category.
-
D.
languageAssociation
chosen
Indicates an association or relationship between entities based on a language they use, represent, or are linked to.
-
E.
languageUsedInLocality
Indicates that a particular language is used or spoken within a specific locality or geographic area.
- 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_69f0ef84e5d08190a0df17f5930ceed3 |
completed | April 28, 2026, 5:33 p.m. |
| NER | Named-entity recognition | batch_69feb5e66224819083b87c3707a5a5e0 |
completed | May 9, 2026, 4:19 a.m. |
| PD | Predicate disambiguation | batch_69feb3bd700c8190991ed200cd3c04db |
completed | May 9, 2026, 4:10 a.m. |
Created at: April 28, 2026, 6:19 p.m.