Triple
T21224338
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ARP (Allocation and Retention Priority) |
E523051
|
entity |
| Predicate | priorityLevelRange |
P52168
|
FINISHED |
| Object | 1 to 15 |
—
|
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: 1 to 15 | Statement: [ARP (Allocation and Retention Priority), priorityLevelRange, 1 to 15]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: priorityLevelRange Context triple: [ARP (Allocation and Retention Priority), priorityLevelRange, 1 to 15]
-
A.
rankRange
Indicates that an entity’s rank falls within a specified minimum and maximum range.
-
B.
limitsPriorityOf
chosen
Indicates that one entity imposes a maximum allowable priority level on another entity’s priority.
-
C.
yLevelRange
Indicates that one entity’s vertical position or height falls within a specified range relative to another entity or reference level.
-
D.
ordinationLevel
Indicates the hierarchical rank or degree of authority assigned to an entity within an ordered or structured system.
-
E.
levels
Indicates that one entity adjusts, equalizes, or smooths out the height, intensity, or degree of another entity.
- 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_69e0b512ad94819087942b2ed925185f |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e734a9c9f88190817b574f916886e5 |
completed | April 21, 2026, 8:26 a.m. |
| PD | Predicate disambiguation | batch_69e5f60e1a888190ba75e2e900270a4e |
completed | April 20, 2026, 9:46 a.m. |
Created at: April 16, 2026, 3:44 p.m.