Triple
T27553764
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deptford Town Hall |
E695578
|
entity |
| Predicate | hasArchitecturalTheme |
P176291
|
FINISHED |
| Object | maritime |
—
|
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: maritime | Statement: [Deptford Town Hall, hasArchitecturalTheme, maritime]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasArchitecturalTheme Context triple: [Deptford Town Hall, hasArchitecturalTheme, maritime]
-
A.
hasArchitecturalFeature
Indicates that one entity possesses, includes, or is characterized by a specific architectural feature or element.
-
B.
hasArchitecturalSignificance
Indicates that something possesses notable architectural qualities, importance, or influence that make it worthy of special attention or recognition.
-
C.
hasArchitecturalDevelopment
Indicates that one entity is responsible for or associated with the architectural development or design of another entity.
-
D.
architecturalStyle
Indicates the architectural design tradition, movement, or style that characterizes the form and appearance of a structure or built work.
-
E.
architecturalConcept
Indicates that one entity represents or embodies an architectural concept in relation to another entity.
- 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_69ef5387e97c8190a9dab040d21cd048 |
completed | April 27, 2026, 12:16 p.m. |
| NER | Named-entity recognition | batch_69f6dfcafd0c81908d86662948c539d6 |
completed | May 3, 2026, 5:40 a.m. |
| PD | Predicate disambiguation | batch_69f6de07836481908785cde9c511920b |
completed | May 3, 2026, 5:32 a.m. |
| PDg | Predicate description generation | batch_69f6df418f488190a5e7ff41f32dceda |
completed | May 3, 2026, 5:38 a.m. |
Created at: April 27, 2026, 1:36 p.m.