Triple
T366015
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ministry of the Interior building |
E7960
|
entity |
| Predicate | hasFacadeFeature |
P6684
|
FINISHED |
| Object | Che Guevara mural |
—
|
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: Che Guevara mural | Statement: [Ministry of the Interior building, hasFacadeFeature, Che Guevara mural]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFacadeFeature Context triple: [Ministry of the Interior building, hasFacadeFeature, Che Guevara mural]
-
A.
hasFeature
Indicates that an entity possesses, exhibits, or includes a particular characteristic, attribute, or component.
-
B.
supportsFeature
Indicates that one entity provides, enables, or is compatible with a particular feature or capability of another.
-
C.
hasFront
Indicates that an entity possesses or is associated with a front-facing side, surface, or portion.
-
D.
hasAspectSystem
Indicates that an entity possesses or is associated with a particular aspect system, such as a structured set of characteristics, dimensions, or perspectives.
-
E.
hasArchitecturalFeature
chosen
Indicates that one entity possesses, includes, or is characterized by a specific architectural feature or element.
- 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_69a2e7e880008190a6ad7e06e5d03007 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ebe7d4d0819083daeb7686ae1914 |
completed | Feb. 28, 2026, 1:21 p.m. |
| PD | Predicate disambiguation | batch_69a2e95dbb208190b277fc5352a4ee84 |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.