Triple
T6292762
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spanish Colonial architecture |
E141057
|
entity |
| Predicate | hasTypicalStructuralElement |
P63681
|
FINISHED |
| Object | wooden beam |
—
|
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: wooden beam | Statement: [Spanish Colonial architecture, hasTypicalStructuralElement, wooden beam]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalStructuralElement Context triple: [Spanish Colonial architecture, hasTypicalStructuralElement, wooden beam]
-
A.
hasHumanStructure
Indicates that one entity possesses or exhibits a structural form or organization characteristic of humans.
-
B.
hasStructureType
Indicates that an entity possesses or is classified by a specific structural type or configuration.
-
C.
hasElementType
chosen
Indicates that something is composed of or contains elements that are of a specified type.
-
D.
hasStructureAbove
Indicates that one entity has another entity positioned vertically higher or located on top of it within a structural or spatial arrangement.
-
E.
hasSignificantStructure
Indicates that an entity possesses a structure or internal organization that is notably complex, important, or meaningful in a given context.
- 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.