Triple
T13496770
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | German telephone numbering plan |
E320781
|
entity |
| Predicate | mobilePrefixExample |
P110648
|
FINISHED |
| Object | 0151 |
—
|
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: 0151 | Statement: [German telephone numbering plan, mobilePrefixExample, 0151]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mobilePrefixExample Context triple: [German telephone numbering plan, mobilePrefixExample, 0151]
-
A.
telecommunicationsProvider
Indicates that one entity provides telecommunications services (such as phone, internet, or data connectivity) to another entity.
-
B.
telephoneStandard
Indicates that there is a relationship involving the use of a particular telephone standard or protocol for communication between entities.
-
C.
callingCode
Indicates the telephone country or area code associated with an entity for making phone calls.
-
D.
addressExamplePrefix
Indicates that an address example is introduced or categorized by a specific prefix string used to distinguish or group it.
-
E.
mobileVariant
Indicates that one entity is a mobile-specific version or adaptation of another entity.
- F. None of above. chosen
Provenance (4 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. |
| PDg | Predicate description generation | batch_69dbaecc98cc8190829f5be759c4f1e3 |
completed | April 12, 2026, 2:40 p.m. |
Created at: April 9, 2026, 9:43 p.m.