Triple
T13496794
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | German telephone numbering plan |
E320781
|
entity |
| Predicate | nationalDestinationCodeLengthRange |
P110656
|
FINISHED |
| Object | 2 to 5 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: 2 to 5 digits | Statement: [German telephone numbering plan, nationalDestinationCodeLengthRange, 2 to 5 digits]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nationalDestinationCodeLengthRange Context triple: [German telephone numbering plan, nationalDestinationCodeLengthRange, 2 to 5 digits]
-
A.
locationCodeMeaning
Indicates the semantic description or interpretation associated with a specific location code.
-
B.
regionCodeType
Indicates the classification or format type used for a given region code within a coding or identification system.
-
C.
touristCorridorLength
Indicates the measured length or extent of a designated tourist corridor or route.
-
D.
capitalOfCountryServed
Indicates that a city serves as the capital of a given country.
-
E.
isResortDestinationFor
Indicates that a place serves as a resort destination specifically intended for or frequented by a particular person, group, or 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.