Triple
T22514903
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Italian telephone numbering plan |
E556614
|
entity |
| Predicate | numberFormatExampleGeographic |
P83564
|
FINISHED |
| Object | +39 011 1234567 |
—
|
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: +39 011 1234567 | Statement: [Italian telephone numbering plan, numberFormatExampleGeographic, +39 011 1234567]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberFormatExampleGeographic Context triple: [Italian telephone numbering plan, numberFormatExampleGeographic, +39 011 1234567]
-
A.
countrySpecificFormat
Indicates that something follows a format or structure that is specific to, and varies by, a particular country.
-
B.
internationalFormat
Indicates that a value is expressed using a standardized international representation or notation, rather than a local or regional format.
-
C.
roundFormat
Indicates the specific structure, rules, or style in which a particular round of an event, game, or process is conducted.
-
D.
coordinateFormat
Indicates the specific representation or notation used to express a set of coordinates.
-
E.
valueFormatExample
chosen
Indicates an example of how a value should be formatted or represented.
- 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.