Triple
T13496767
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | German telephone numbering plan |
E320781
|
entity |
| Predicate | nationalSignificantNumberStructure |
P110645
|
FINISHED |
| Object | area code + subscriber number |
—
|
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: area code + subscriber number | Statement: [German telephone numbering plan, nationalSignificantNumberStructure, area code + subscriber number]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nationalSignificantNumberStructure Context triple: [German telephone numbering plan, nationalSignificantNumberStructure, area code + subscriber number]
-
A.
regionNumber
Indicates that an entity is assigned to or associated with a specific numbered region within a larger spatial or organizational division.
-
B.
provinceNumber
Indicates a relationship where an entity is assigned a specific numerical identifier corresponding to a province.
-
C.
administrativeNumber
Indicates that an entity is associated with a specific official identification or reference number used for administrative purposes.
-
D.
censusNumber
Indicates the unique identifier or count assigned to an entity within an official census record.
-
E.
SSNumber
Indicates that an entity has a specific Social Security Number assigned to it.
- 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.