Triple
T35738536
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | London Road (Norbury) |
E1032962
|
entity |
| Predicate | hasStreetFrontage |
P106122
|
FINISHED |
| Object | retail units |
—
|
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: retail units | Statement: [London Road (Norbury), hasStreetFrontage, retail units]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStreetFrontage Context triple: [London Road (Norbury), hasStreetFrontage, retail units]
-
A.
hasStreetFront
Indicates that one entity directly borders or faces onto a particular street along its frontage.
-
B.
streetFrontageOn
chosen
Indicates that a property or parcel directly borders or faces a particular street along at least one of its sides.
-
C.
hasFrontageRoads
Indicates that a primary road or highway is accompanied by one or more adjacent frontage roads running alongside it.
-
D.
hasTypicalFrontage
Indicates that something normally faces or fronts onto something else, such as a property having its usual frontage on a particular street or area.
-
E.
hasStreet
Indicates that an entity is located on, associated with, or identified by a particular street.
- 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_69f76e10e59081908d81ad9ce22f40b6 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a000fda03948190881b7275f249768f |
completed | May 10, 2026, 4:55 a.m. |
| PD | Predicate disambiguation | batch_6a000f607f1881908ee750d58da91690 |
completed | May 10, 2026, 4:53 a.m. |
Created at: May 3, 2026, 4:05 p.m.