Triple
T1170395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Supreme Federal Court building in Brasília |
E24896
|
entity |
| Predicate | hasGlazedGroundFloor |
P11118
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Supreme Federal Court building in Brasília, hasGlazedGroundFloor, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGlazedGroundFloor Context triple: [Supreme Federal Court building in Brasília, hasGlazedGroundFloor, yes]
-
A.
hasGlassFloor
Indicates that one entity possesses or features a floor made of glass.
-
B.
hasFloorMaterial
chosen
Indicates that an entity’s floor is made of, covered with, or constructed from a specified material.
-
C.
hasFlooring
Indicates that one entity is equipped with or covered by a particular type of flooring material provided by another entity.
-
D.
hasFloor
Indicates that one entity possesses, includes, or is associated with a particular floor or level within a structure.
-
E.
floorType
Indicates the type or material classification of a floor associated with an entity.
- 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_69a494082a7c819095004f423f294a64 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bce972cc8190bce0b77cfda6da41 |
completed | March 1, 2026, 10:25 p.m. |
| PD | Predicate disambiguation | batch_69a4bb5656948190b0b1d5446ad06005 |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:45 p.m.