Triple
T21205375
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belm |
E522562
|
entity |
| Predicate | telephoneDialingCodeSystem |
P143537
|
FINISHED |
| Object | German area code |
—
|
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: German area code | Statement: [Belm, telephoneDialingCodeSystem, German area code]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: telephoneDialingCodeSystem Context triple: [Belm, telephoneDialingCodeSystem, German area code]
-
A.
callingCode
Indicates the telephone country or area code associated with an entity for making phone calls.
-
B.
callingCodeType
Indicates the type or category of a telephone calling code associated with an entity.
-
C.
continentCode
Indicates the standardized code assigned to the continent with which an entity is associated.
-
D.
telephoneStandard
Indicates that there is a relationship involving the use of a particular telephone standard or protocol for communication between entities.
-
E.
nationalPrefixForDomesticCalls
Indicates the dialing prefix that must be used when making domestic telephone calls within a given country or numbering plan.
- 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_69e0b5112d8881909510b2dcdc93106d |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e734342e9081909e241bed54dbc0b4 |
completed | April 21, 2026, 8:24 a.m. |
| PD | Predicate disambiguation | batch_69e5f6094e3c81909ee9699e00d371f7 |
completed | April 20, 2026, 9:46 a.m. |
| PDg | Predicate description generation | batch_69e5fa92a2448190896c022dd27511ad |
completed | April 20, 2026, 10:06 a.m. |
Created at: April 16, 2026, 3:20 p.m.