Triple
T6227261
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bezirk Berlin |
E139264
|
entity |
| Predicate | hadTelephoneCode |
P190
|
FINISHED |
| Object | East German telephone system |
—
|
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: East German telephone system | Statement: [Bezirk Berlin, hadTelephoneCode, East German telephone system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadTelephoneCode Context triple: [Bezirk Berlin, hadTelephoneCode, East German telephone system]
-
A.
hasTelephoneService
Indicates that a subject is provided with or connected to telephone service.
-
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.
hasCallInNumber
Indicates that an entity has an associated telephone number designated for receiving incoming calls.
-
D.
callingCode
Indicates the telephone country or area code associated with an entity for making phone calls.
-
E.
areaCode
Indicates that a location, phone number, or region is associated with a specific telephone 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_69c008afd3148190b71e9eaa60420dd1 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c062d686b88190a0e7e38ab52e2d4a |
completed | March 22, 2026, 9:44 p.m. |
| PD | Predicate disambiguation | batch_69c055ffdf54819086d987d646e44ff5 |
completed | March 22, 2026, 8:50 p.m. |
Created at: March 22, 2026, 4:22 p.m.