Triple
T21287285
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 3GPP TS 24.301 |
E524693
|
entity |
| Predicate | usedBy |
P260
|
FINISHED |
| Object | User Equipment |
—
|
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: User Equipment | Statement: [3GPP TS 24.301, usedBy, User Equipment]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: User Equipment Context triple: [3GPP TS 24.301, usedBy, User Equipment]
-
A.
User Equipment
chosen
User Equipment is the end-user mobile device in cellular networks (such as phones, tablets, or modems) that provides radio connectivity and access to network services over technologies like UMTS and LTE.
-
B.
Device
Device is the surname of Anathema Device, a witch and key character in Neil Gaiman and Terry Pratchett’s novel "Good Omens."
-
C.
Device Stage
Device Stage is a Windows feature that provides a centralized, task-based interface for managing and interacting with connected devices such as printers, cameras, and phones.
-
D.
Gadget
Gadget is the bumbling yet well-intentioned cyborg detective protagonist of the animated series "Inspector Gadget," known for his numerous built-in mechanical devices.
-
E.
Device Solutions
Device Solutions is a major Samsung division responsible for its core semiconductor and component businesses, including memory chips and system LSI.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b5171f6c8190a5d57201ede73811 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e736d717c88190950bd48058912b65 |
completed | April 21, 2026, 8:35 a.m. |
Created at: April 16, 2026, 4:03 p.m.