Triple
T4696017
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Islington, London, England |
E104143
|
entity |
| Predicate | hasLondonDialingCode |
P190
|
FINISHED |
| Object | 020 |
—
|
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: 020 | Statement: [Islington, London, England, hasLondonDialingCode, 020]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLondonDialingCode Context triple: [Islington, London, England, hasLondonDialingCode, 020]
-
A.
hasAreaCodeCountry
Indicates that a particular telephone area code is associated with or belongs to a specific country.
-
B.
callingCode
Indicates the telephone country or area code associated with an entity for making phone calls.
-
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.
callingCodeType
Indicates the type or category of a telephone calling code associated with an entity.
-
E.
UICCountryCode
Indicates that an entity is associated with a specific country identified by its UIC (International Union of Railways) country 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_69bd43df91f481908e9add1b617b60ef |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd650ad0f88190844bfcb46b3071c2 |
completed | March 20, 2026, 3:17 p.m. |
| PD | Predicate disambiguation | batch_69bd621ba7448190a53ab1e2897acf71 |
completed | March 20, 2026, 3:04 p.m. |
Created at: March 20, 2026, 1:17 p.m.