Triple
T627532
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Temuco |
E15850
|
entity |
| Predicate | callingCodeType |
P17236
|
FINISHED |
| Object | Chilean telephone numbering plan |
—
|
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: Chilean telephone numbering plan | Statement: [Temuco, callingCodeType, Chilean telephone numbering plan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: callingCodeType Context triple: [Temuco, callingCodeType, Chilean telephone numbering plan]
-
A.
callingCode
Indicates the telephone country or area code associated with an entity for making phone calls.
-
B.
areaCode
Indicates that a location, phone number, or region is associated with a specific telephone area code.
-
C.
regionCodeType
Indicates the classification or format type used for a given region code within a coding or identification system.
-
D.
callSignType
Indicates the classification or category of a call sign associated with an entity or communication.
-
E.
hasAreaCodeType
Indicates that an entity’s area code is associated with a specific type or classification of area code.
- F. None of above. chosen
Provenance (4 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_69a4935c131c8190a5378c6bf101e8cc |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49e59e2688190b3c18b17c5db1e2b |
completed | March 1, 2026, 8:15 p.m. |
| PD | Predicate disambiguation | batch_69a49d01b29081908be87e4cd7726ff1 |
completed | March 1, 2026, 8:09 p.m. |
| PDg | Predicate description generation | batch_69a49defe58c8190bd39ef47c9f660a7 |
completed | March 1, 2026, 8:13 p.m. |
Created at: March 1, 2026, 7:35 p.m.