Triple
T18127717
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wallesau |
E433921
|
entity |
| Predicate | areaCodeAreaOf |
P190
|
FINISHED |
| Object | 09171 |
—
|
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: 09171 | Statement: [Wallesau, areaCodeAreaOf, 09171]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: areaCodeAreaOf Context triple: [Wallesau, areaCodeAreaOf, 09171]
-
A.
areaCode
Indicates that a location, phone number, or region is associated with a specific telephone area code.
-
B.
countyArea
Indicates the total geographic area covered by a county, typically measured in standard area units.
-
C.
hasAreaCode
chosen
Indicates that a specified telephone area code is assigned to or associated with a particular geographic region, location, or phone service entity.
-
D.
statisticalAreaOf
Indicates that one entity is the designated statistical area or region associated with, containing, or characterizing another entity for statistical or demographic purposes.
-
E.
hasAreaNumber
Indicates that an entity is associated with a specific area identified by a numerical 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_69d8b909e8cc81908df4cc2b8ea6d11f |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ddef4cd88190b16ef0d6ed3968c6 |
completed | April 19, 2026, 1:51 p.m. |
| PD | Predicate disambiguation | batch_69e43313ca788190baa224269e71de49 |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:29 a.m.