Triple
T5771090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NB-IoT |
E127331
|
entity |
| Predicate | supportsCellRange |
P49736
|
FINISHED |
| Object | up to about 10–15 km (rural, typical) |
—
|
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: up to about 10–15 km (rural, typical) | Statement: [NB-IoT, supportsCellRange, up to about 10–15 km (rural, typical)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsCellRange Context triple: [NB-IoT, supportsCellRange, up to about 10–15 km (rural, typical)]
-
A.
hasCells
Indicates that an entity contains, is composed of, or is associated with one or more cells.
-
B.
hasRange
Indicates that a property or relation is constrained to take its values from a specified class, type, or value set.
-
C.
designedRange
chosen
Indicates the intended or specified range within which something is designed to operate or be effective.
-
D.
numberOfCells
Indicates the total count of individual cells associated with or contained in a given entity.
-
E.
nativeRange
Indicates the geographic area where an entity naturally occurs or originated without human introduction.
- 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_69c00834f6308190851b0abeddd8ed7e |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02acb12c081908e4beee4a957f9f9 |
completed | March 22, 2026, 5:45 p.m. |
| PD | Predicate disambiguation | batch_69c021ce8d3c81909b332cb1c33a61ad |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:50 p.m.