Triple
T80614
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shrewsbury, Shropshire, England |
E1618
|
entity |
| Predicate | hasDialCode |
P190
|
FINISHED |
| Object | 01743 |
—
|
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: 01743 | Statement: [Shrewsbury, Shropshire, England, hasDialCode, 01743]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDialCode Context triple: [Shrewsbury, Shropshire, England, hasDialCode, 01743]
-
A.
callingCode
Indicates the telephone country or area code associated with an entity for making phone calls.
-
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.
areaCode
Indicates that a location, phone number, or region is associated with a specific telephone area code.
-
D.
numericCode
Indicates that an entity is associated with a specific numerical identifier or classification code.
-
E.
hasISOCode
Indicates that an entity is associated with a specific standardized ISO code that uniquely identifies it according to ISO conventions.
- 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_69a24c60d19c8190a1b6c105ca59ef5b |
completed | Feb. 28, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69a25053ca208190a371b0d38000c2b9 |
completed | Feb. 28, 2026, 2:17 a.m. |
| PD | Predicate disambiguation | batch_69a24eb2998c819082681da74601d446 |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 2:06 a.m.