Triple
T17117306
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Newcastle city centre |
E415372
|
entity |
| Predicate | hasPrimaryStreetType |
P99920
|
FINISHED |
| Object | pedestrianised shopping streets |
—
|
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: pedestrianised shopping streets | Statement: [Newcastle city centre, hasPrimaryStreetType, pedestrianised shopping streets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimaryStreetType Context triple: [Newcastle city centre, hasPrimaryStreetType, pedestrianised shopping streets]
-
A.
isPrimarySurfaceStreetIn
chosen
Indicates that a street serves as a main or primary surface-level roadway within a specified area or jurisdiction.
-
B.
hasSideStreetType
Indicates that an entity (such as a street or road segment) is associated with a specific type or classification of side street.
-
C.
hasMainResidentialStreet
Indicates that an entity is associated with or served by a specific primary street used predominantly for residential purposes.
-
D.
hasStreet
Indicates that an entity is located on, associated with, or identified by a particular street.
-
E.
hasSecondaryStreet
Indicates that an entity is associated with an additional, non-primary street address or roadway.
- 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_69d886d090cc8190a39cb94992586905 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3e8075a6c8190954d36eb94d1028a |
completed | April 18, 2026, 8:22 p.m. |
| PD | Predicate disambiguation | batch_69e35d6b1b988190a8d6b6fe78c35e59 |
completed | April 18, 2026, 10:31 a.m. |
Created at: April 10, 2026, 5:35 a.m.