Triple
T2637001
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wokingham |
E59768
|
entity |
| Predicate | hasTownCentreType |
P35906
|
FINISHED |
| Object | traditional town centre |
—
|
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: traditional town centre | Statement: [Wokingham, hasTownCentreType, traditional town centre]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTownCentreType Context triple: [Wokingham, hasTownCentreType, traditional town centre]
-
A.
hasCityCentreLocation
Indicates that something is located in, or directly associated with, the central area of a city.
-
B.
hasShoppingDistrictType
chosen
Indicates that an entity is associated with a particular type or category of shopping district.
-
C.
hasCircuitCentre
Indicates that an entity has, is associated with, or is organized around a specific circuit center that serves as its focal or central point.
-
D.
hasTown
Indicates that one entity possesses, contains, or is associated with a town as part of its structure, jurisdiction, or composition.
-
E.
hasMunicipalityType
Indicates that an administrative unit is classified as having a specific type or category of municipality (e.g., city, town, village).
- 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_69ab4ac8596c8190b34997e73d9e991c |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd8e3190081908ea828fe79569cc9 |
completed | March 7, 2026, 7:50 a.m. |
| PD | Predicate disambiguation | batch_69abd812849881908f956845a80e0205 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:50 p.m.