Triple
T776203
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thuja |
E16390
|
entity |
| Predicate | typicalUseContext |
P12230
|
FINISHED |
| Object | gardens |
—
|
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: gardens | Statement: [Thuja, typicalUseContext, gardens]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalUseContext Context triple: [Thuja, typicalUseContext, gardens]
-
A.
contextOf
Indicates that one entity provides the situational, informational, or environmental background within which another entity exists, occurs, or is interpreted.
-
B.
usageType
Indicates the specific manner, purpose, or context in which something is used or intended to be used.
-
C.
canonicalContext
Indicates the standard or primary contextual framework within which an entity, statement, or resource is to be interpreted.
-
D.
scopeOfUse
Indicates the range, context, or conditions under which something is intended, allowed, or applicable to be used.
-
E.
typicalIn
chosen
Indicates that something commonly occurs, appears, or is found within a given context, category, or environment.
- 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_69a49369a0848190af883934cee3db4c |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a74da7648190adfad56717d564df |
completed | March 1, 2026, 8:53 p.m. |
| PD | Predicate disambiguation | batch_69a4a50a443481909ae3662764ee69a4 |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.