Triple
T359372
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Indiana limestone |
E7813
|
entity |
| Predicate | typicalApplication |
P2529
|
FINISHED |
| Object | load-bearing masonry |
—
|
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: load-bearing masonry | Statement: [Indiana limestone, typicalApplication, load-bearing masonry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalApplication Context triple: [Indiana limestone, typicalApplication, load-bearing masonry]
-
A.
usageType
chosen
Indicates the specific manner, purpose, or context in which something is used or intended to be used.
-
B.
typicalFeatures
Indicates that the related entities are characteristic or commonly occurring features or attributes of something.
-
C.
appliesTo
Indicates that something is relevant, valid, or has effect in relation to a particular entity, case, or context.
-
D.
standardApplied
Indicates that a particular standard, rule, or guideline has been put into effect or used as the basis for an action or decision in the relationship.
-
E.
typicalDeployment
Indicates that one entity represents the standard or most commonly used deployment configuration or pattern for the other 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_69a2e7e880008190a6ad7e06e5d03007 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ebb248608190b060553219616043 |
completed | Feb. 28, 2026, 1:20 p.m. |
| PD | Predicate disambiguation | batch_69a2e95aeed48190b5e48865cc964938 |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.