Triple
T6292767
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spanish Colonial architecture |
E141057
|
entity |
| Predicate | hasTypicalSpace |
P32186
|
FINISHED |
| Object | central patio |
—
|
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: central patio | Statement: [Spanish Colonial architecture, hasTypicalSpace, central patio]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalSpace Context triple: [Spanish Colonial architecture, hasTypicalSpace, central patio]
-
A.
hasSpaceType
chosen
Indicates that one entity is associated with, or classified by, a particular type or category of space.
-
B.
hasCentralSpace
Indicates that an entity includes or is characterized by a primary, central area or space within its overall structure.
-
C.
isWrittenWithSpace
Indicates that something is written or represented with spaces separating its components or elements.
-
D.
hasPublicSpaceAlong
Indicates that a public space (such as a park, plaza, or walkway) is located adjacent to or runs alongside the referenced feature or element.
-
E.
hasTypicalCharacterType
Indicates that an entity is commonly associated with or exemplified by a particular type of character or persona.
- 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_69c008cdf2ac8190bb640c94478fb4ed |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0642017588190b6c99c685653f6c2 |
completed | March 22, 2026, 9:50 p.m. |
| PD | Predicate disambiguation | batch_69c060df0d8881908215575862ef6831 |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:27 p.m.