Triple
T12472485
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arsk |
E298093
|
entity |
| Predicate | hasDialingCodeType |
P17236
|
FINISHED |
| Object | Russian telephone 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: Russian telephone area code | Statement: [Arsk, hasDialingCodeType, Russian telephone area code]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDialingCodeType Context triple: [Arsk, hasDialingCodeType, Russian telephone area code]
-
A.
hasIslandDialingCode
Indicates that an island is associated with a particular telephone dialing code used for placing calls to it.
-
B.
callingCodeType
chosen
Indicates the type or category of a telephone calling code associated with an entity.
-
C.
hasAreaCodeType
Indicates that an entity’s area code is associated with a specific type or classification of area code.
-
D.
hasAreaCodeCountry
Indicates that a particular telephone area code is associated with or belongs to a specific country.
-
E.
isCountryCode
Indicates that one entity is a valid country code designating the country represented by the other entity.
- 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_69d6ada270808190b1a2b2e7b02bb426 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94e626dbc8190ac7dcdb542ba9b0c |
completed | April 10, 2026, 7:24 p.m. |
| PD | Predicate disambiguation | batch_69d94d3f701c81909dd0e00251ac8553 |
completed | April 10, 2026, 7:19 p.m. |
Created at: April 8, 2026, 9:56 p.m.