Triple
T13496762
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | German telephone numbering plan |
E320781
|
entity |
| Predicate | maximumNationalNumberLength |
P110644
|
FINISHED |
| Object | 13 digits |
—
|
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: 13 digits | Statement: [German telephone numbering plan, maximumNationalNumberLength, 13 digits]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumNationalNumberLength Context triple: [German telephone numbering plan, maximumNationalNumberLength, 13 digits]
-
A.
countryCodeLength
Indicates the number of characters that a given country code consists of.
-
B.
telephoneStandard
Indicates that there is a relationship involving the use of a particular telephone standard or protocol for communication between entities.
-
C.
countryCodeFormat
Indicates the standardized structure or pattern in which a country's code must be represented.
-
D.
telephoneNumberingPlan
Indicates a relationship where a telephone numbering plan defines or governs how telephone numbers are structured, assigned, or managed for a given telecommunication context.
-
E.
callingCode
Indicates the telephone country or area code associated with an entity for making phone calls.
- 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.