Triple
T2310675
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St Peter's Square, Manchester |
E51948
|
entity |
| Predicate | hasPedestrianisationStatus |
P18406
|
FINISHED |
| Object | largely pedestrianised |
—
|
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: largely pedestrianised | Statement: [St Peter's Square, Manchester, hasPedestrianisationStatus, largely pedestrianised]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPedestrianisationStatus Context triple: [St Peter's Square, Manchester, hasPedestrianisationStatus, largely pedestrianised]
-
A.
pedestrianRestrictions
Indicates that there are specific rules or limitations governing where or how pedestrians may travel or access an area.
-
B.
hasPedestrianAccessTo
Indicates that a location or area can be reached or entered safely and directly by people on foot.
-
C.
hasPedestrianPlazaOn
Indicates that a pedestrian plaza is located on, or directly associated with, a specified surface, structure, or area.
-
D.
hasPedestrianArea
chosen
Indicates that a location or zone includes a designated area intended for pedestrian use only or primarily.
-
E.
hasPedestrianPriority
Indicates that pedestrians are given precedence or right-of-way over other road users in a particular context or area.
- 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_69a88b0bb30c81908ded03b006d29387 |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abc685f05481909c863b29d1f6bacd |
completed | March 7, 2026, 6:32 a.m. |
| PD | Predicate disambiguation | batch_69abc58e88e481908733fdf79d3f8a15 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:49 p.m.