Triple
T5480050
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VoLTE |
E123445
|
entity |
| Predicate | usesAccessTechnology |
P41801
|
FINISHED |
| Object | OFDMA on downlink |
—
|
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: OFDMA on downlink | Statement: [VoLTE, usesAccessTechnology, OFDMA on downlink]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesAccessTechnology Context triple: [VoLTE, usesAccessTechnology, OFDMA on downlink]
-
A.
usesDevice
Indicates that one entity operates, employs, or relies on a particular device to perform an action or achieve a purpose.
-
B.
technologyUse
chosen
Indicates the use or application of a particular technology by an entity to perform an action or achieve a purpose.
-
C.
usesEquipment
Indicates that an entity employs or operates a particular piece of equipment to perform an action or fulfill a function.
-
D.
technologyUsedIn
Indicates that a particular technology is employed or applied within a specific process, product, context, or domain.
-
E.
associatedWithTechnology
Indicates a relationship where an entity is connected to, involved with, or utilizes a particular technology.
- 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_69bd4648883481909e9775d43300c5fa |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd9248ca348190aa116cace0f9b07a |
completed | March 20, 2026, 6:30 p.m. |
| PD | Predicate disambiguation | batch_69bd91a58c448190904964a439045e05 |
completed | March 20, 2026, 6:27 p.m. |
Created at: March 20, 2026, 2:09 p.m.