Triple
T7836367
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CCNP Voice |
E181698
|
entity |
| Predicate | levelInTrack |
P4144
|
FINISHED |
| Object | professional |
—
|
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: professional | Statement: [CCNP Voice, levelInTrack, professional]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: levelInTrack Context triple: [CCNP Voice, levelInTrack, professional]
-
A.
levels
Indicates that one entity adjusts, equalizes, or smooths out the height, intensity, or degree of another entity.
-
B.
levelNotation
Indicates the specific symbolic or textual notation used to represent the level, degree, or rank of something within a defined scale or hierarchy.
-
C.
railroadHierarchyLevel
Indicates the position or rank of a railroad-related entity within an ordered organizational or structural hierarchy.
-
D.
trainingLevel
chosen
Indicates the degree or stage of training or skill development that an entity has attained.
-
E.
focusLevel
Indicates the degree or intensity of attention or concentration directed toward a particular target or task.
- 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_69ca8284a25c8190a1a20afad30da792 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb064cb7e081909e88419863d94dfe |
completed | March 30, 2026, 11:25 p.m. |
| PD | Predicate disambiguation | batch_69cae91e98988190abd4ece75932c589 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 4:46 p.m.