Triple
T13496788
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | German telephone numbering plan |
E320781
|
entity |
| Predicate | definesNumberRangesFor |
P36590
|
FINISHED |
| Object | fixed-line services |
—
|
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: fixed-line services | Statement: [German telephone numbering plan, definesNumberRangesFor, fixed-line services]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: definesNumberRangesFor Context triple: [German telephone numbering plan, definesNumberRangesFor, fixed-line services]
-
A.
rangeOf
Indicates that one entity specifies the set of possible values (range) that another entity’s outputs or properties can take.
-
B.
introducedRange
Indicates that an entity has brought a particular range (such as a span, interval, or set of values) into existence, use, or consideration.
-
C.
includesNumberingRange
chosen
Indicates that one entity contains or covers a specified contiguous range of numbers associated with another entity.
-
D.
designedRange
Indicates the intended or specified range within which something is designed to operate or be effective.
-
E.
hasRange
Indicates that a property or relation is constrained to take its values from a specified class, type, or value set.
- 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_69d807629d6c8190998f1b9bb12d2ed0 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaf4e9ca4819083116890a65389f9 |
completed | April 12, 2026, 2:42 p.m. |
| PD | Predicate disambiguation | batch_69dbae06061881909a6a6032e0507587 |
completed | April 12, 2026, 2:36 p.m. |
Created at: April 9, 2026, 9:43 p.m.