Triple
T1077603
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RAN |
E23872
|
entity |
| Predicate | hasSubgroup |
P747
|
FINISHED |
| Object | RAN2 |
E23872
|
NE 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: RAN2 | Statement: [RAN, hasSubgroup, RAN2]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: RAN2 Context triple: [RAN, hasSubgroup, RAN2]
-
A.
RAN
chosen
RAN is the 3GPP working group responsible for specifying the radio access network technologies used in mobile communication systems such as LTE and 5G.
-
B.
Rycken
Rycken is a Dutch-origin surname historically borne by families such as that of Abraham Rycken in the Low Countries and early colonial America.
-
C.
Runasimi
Runasimi is the Indigenous Quechuan language family of the Andes, historically associated with the Inca Empire and still widely spoken across several South American countries.
-
D.
Rappen
Rappen is the German term for the centime-like subunit of the Swiss franc, used to denote its smaller denominations.
-
E.
R4
R4 is a government office building in Oslo that forms part of Norway’s central Regjeringskvartalet complex.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a493f1ddf48190a99d54b00e99f8ce |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b94288d88190aae4fb86236c0702 |
completed | March 1, 2026, 10:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac42abc7a08190a34f5b2d393db30e |
completed | March 7, 2026, 3:22 p.m. |
Created at: March 1, 2026, 7:42 p.m.