Triple
T6608827
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Granada Studios |
E149184
|
entity |
| Predicate | streetSet |
P72421
|
FINISHED |
| Object | Coronation Street set |
—
|
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: Coronation Street set | Statement: [Granada Studios, streetSet, Coronation Street set]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: streetSet Context triple: [Granada Studios, streetSet, Coronation Street set]
-
A.
betweenStreets
Indicates that one location is situated between two specified streets, typically along a road segment bounded by those streets.
-
B.
hasStreet
Indicates that an entity is located on, associated with, or identified by a particular street.
-
C.
streetNetwork
Indicates the layout and connectivity relationships among streets within a geographic area, including how roads intersect, link, and form a navigable network.
-
D.
streetFunction
Indicates the functional role or primary use of a street within a transportation or urban context (e.g., residential, arterial, commercial access).
-
E.
roadName
Indicates the specific name assigned to a road that identifies it within a transportation or address system.
- F. None of above. chosen
Provenance (4 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_69c687ebc680819094caf71faba2efe2 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6cf3796d08190a26e988386089447 |
completed | March 27, 2026, 6:40 p.m. |
| PD | Predicate disambiguation | batch_69c6acfed25481909cac74c84a9fe088 |
completed | March 27, 2026, 4:14 p.m. |
| PDg | Predicate description generation | batch_69c6cf3683d08190b19e2aad30f2800f |
completed | March 27, 2026, 6:40 p.m. |
Created at: March 27, 2026, 1:57 p.m.