Triple
T22514881
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Italian telephone numbering plan |
E556614
|
entity |
| Predicate | nationalSignificantNumberLength |
P110644
|
FINISHED |
| Object | 10 |
—
|
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: 10 | Statement: [Italian telephone numbering plan, nationalSignificantNumberLength, 10]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nationalSignificantNumberLength Context triple: [Italian telephone numbering plan, nationalSignificantNumberLength, 10]
-
A.
nationalSignificantNumberStructure
Indicates the structural format or pattern that a national significant telephone number must follow within a country’s numbering plan.
-
B.
maximumNationalNumberLength
chosen
Indicates the greatest number of digits allowed in a national (domestic) phone number for a given country or numbering plan.
-
C.
countryCodeLength
Indicates the number of characters that a given country code consists of.
-
D.
subscriberNumberLengthRange
Indicates the allowed minimum and maximum length range for a subscriber’s phone number in a given context.
-
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.
Provenance (3 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_69e11e555edc81909ca803587dafd747 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15e2c3098819098a553133cc9515b |
completed | April 29, 2026, 1:26 a.m. |
| PD | Predicate disambiguation | batch_69ee625e3b408190a60c759fb0b28fe2 |
completed | April 26, 2026, 7:07 p.m. |
Created at: April 16, 2026, 8:50 p.m.