Triple
T13496760
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | German telephone numbering plan |
E320781
|
entity |
| Predicate | usesVariableLengthAreaCodes |
P110642
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [German telephone numbering plan, usesVariableLengthAreaCodes, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesVariableLengthAreaCodes Context triple: [German telephone numbering plan, usesVariableLengthAreaCodes, true]
-
A.
hasAreaCode
Indicates that a specified telephone area code is assigned to or associated with a particular geographic region, location, or phone service entity.
-
B.
hasAreaCodeType
Indicates that an entity’s area code is associated with a specific type or classification of area code.
-
C.
hasAreaCodeCountry
Indicates that a particular telephone area code is associated with or belongs to a specific country.
-
D.
areaCode
Indicates that a location, phone number, or region is associated with a specific telephone area code.
-
E.
hasAreaCodeSystem
Indicates that a telephone numbering plan, region, or communication system uses or is associated with a particular area code system.
- 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.