Triple
T25413037
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Square, Buxton |
E636754
|
entity |
| Predicate | roleInTownscape |
P8234
|
FINISHED |
| Object | key element of Buxton’s historic core |
—
|
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: key element of Buxton’s historic core | Statement: [The Square, Buxton, roleInTownscape, key element of Buxton’s historic core]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInTownscape Context triple: [The Square, Buxton, roleInTownscape, key element of Buxton’s historic core]
-
A.
roleInUrbanPlan
Indicates the specific function, responsibility, or position an entity holds within an urban planning context or scheme.
-
B.
roleAsPlace
Indicates that an entity functions or is used as a place or location in relation to another entity or event.
-
C.
urbanDesigner
Indicates a relationship where an entity practices or is responsible for planning and designing urban spaces, environments, or city layouts.
-
D.
roleInDarkCity
Indicates that an entity has a specific role, function, or character within the context of the work "Dark City."
-
E.
hasCityRole
chosen
Indicates that an entity holds or is assigned a specific role, function, or status within a particular city.
- 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_69e75db4135881909acc287ebcb7a505 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f6a8df16a88190a23820e64a3b1f92 |
completed | May 3, 2026, 1:46 a.m. |
| PD | Predicate disambiguation | batch_69f6a751d5e48190a77dcecbe7ef9f0b |
completed | May 3, 2026, 1:39 a.m. |
Created at: April 21, 2026, 1:55 p.m.