Triple
T15115853
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kileler municipality |
E361036
|
entity |
| Predicate | telephoneAreaCodeRegion |
P190
|
FINISHED |
| Object | +30 241x |
—
|
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: +30 241x | Statement: [Kileler municipality, telephoneAreaCodeRegion, +30 241x]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: telephoneAreaCodeRegion Context triple: [Kileler municipality, telephoneAreaCodeRegion, +30 241x]
-
A.
areaCode
Indicates that a location, phone number, or region is associated with a specific telephone area code.
-
B.
hasAreaCode
chosen
Indicates that a specified telephone area code is assigned to or associated with a particular geographic region, location, or phone service entity.
-
C.
icaoRegionPrefix
Indicates the regional ICAO prefix that designates the geographic or administrative region associated with an aviation-related entity.
-
D.
hasAreaCodeCountry
Indicates that a particular telephone area code is associated with or belongs to a specific country.
-
E.
hasAreaCodeType
Indicates that an entity’s area code is associated with a specific type or classification of area code.
- 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_69d85a0491ec8190830960be8fafb994 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0058f4fb88190a3d446a466aebcf1 |
completed | April 15, 2026, 9:39 p.m. |
| PD | Predicate disambiguation | batch_69deb96c1d9c81909351558ed97bc5b7 |
completed | April 14, 2026, 10:02 p.m. |
Created at: April 10, 2026, 3:05 a.m.