Triple
T6305285
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 3GPP RAN |
E141359
|
entity |
| Predicate | RAN1Scope |
P25607
|
FINISHED |
| Object | physical layer aspects |
—
|
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: physical layer aspects | Statement: [3GPP RAN, RAN1Scope, physical layer aspects]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: RAN1Scope Context triple: [3GPP RAN, RAN1Scope, physical layer aspects]
-
A.
ranIn
Indicates that an entity performed a running action within or during a specified location, context, or time frame.
-
B.
operationalScope
Indicates the range, extent, or boundaries within which an entity, process, or activity is authorized or designed to operate.
-
C.
scopeType
chosen
Indicates the specific range, level, or context within which a given relationship, rule, or action is defined or applies.
-
D.
scopeOfReset
Indicates the range or extent within which a reset action applies or takes effect.
-
E.
rangeOf
Indicates that one entity specifies the set of possible values (range) that another entity’s outputs or properties can take.
- 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_69c008cf0ad4819095def81e2bd42f9f |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c06479acec819090306a155a03b774 |
completed | March 22, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69c060e311b48190b1c74a5cf9435623 |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:28 p.m.