Triple
T7478202
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cabildo of Buenos Aires |
E176682
|
entity |
| Predicate | basementUse |
P43526
|
FINISHED |
| Object | museum rooms and cells |
—
|
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: museum rooms and cells | Statement: [Cabildo of Buenos Aires, basementUse, museum rooms and cells]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: basementUse Context triple: [Cabildo of Buenos Aires, basementUse, museum rooms and cells]
-
A.
hasBasementUse
chosen
Indicates that a building or structure’s basement is used for a specified purpose or function.
-
B.
basementType
Indicates the type or classification of a building’s basement as defined in the relationship.
-
C.
hasBasement
Indicates that a building or structure includes a basement level as part of its physical layout.
-
D.
formsBasementFor
Indicates that one entity serves as the foundational or lowest structural layer upon which another entity is built or supported.
-
E.
houseUse
Indicates how a house or dwelling is used or purposed (e.g., residential, commercial, mixed-use).
- 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_69c69f236ce08190a04d7679f03b29b2 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f4f0088c8190880770ac31e5b7a7 |
completed | March 27, 2026, 9:21 p.m. |
| PD | Predicate disambiguation | batch_69c6f03d967081908a8e696ff9693b90 |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:42 p.m.