Triple
T34004768
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dutch telephone numbering plan |
E871928
|
entity |
| Predicate | geographicNumberLength |
P110644
|
FINISHED |
| Object | 10 digits including trunk prefix |
—
|
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 digits including trunk prefix | Statement: [Dutch telephone numbering plan, geographicNumberLength, 10 digits including trunk prefix]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: geographicNumberLength Context triple: [Dutch telephone numbering plan, geographicNumberLength, 10 digits including trunk prefix]
-
A.
countryCodeLength
Indicates the number of characters that a given country code consists of.
-
B.
previousNationalNumberLengths
Indicates that an entity previously used one or more specific lengths for its national (telephone) numbers before a change or update.
-
C.
areaCodeLength
Indicates the number of digits or characters that make up a given area code.
-
D.
maximumNationalNumberLength
chosen
Indicates the greatest number of digits allowed in a national (domestic) phone number for a given country or numbering plan.
-
E.
numericCountryCode
Indicates that a country is associated with a specific numeric code that uniquely identifies it.
- 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_69f349a08848819084b348d64c1879c3 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fb3425666081908916fcbf3b5dd907 |
completed | May 6, 2026, 12:29 p.m. |
| PD | Predicate disambiguation | batch_69fb2f5f3164819099429c2cc3d24e01 |
completed | May 6, 2026, 12:09 p.m. |
Created at: May 1, 2026, 1:50 a.m.