Triple
T23996235
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fit Me loose finishing powder |
E605195
|
entity |
| Predicate | applicationTool |
P154557
|
FINISHED |
| Object | powder brush |
—
|
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: powder brush | Statement: [Fit Me loose finishing powder, applicationTool, powder brush]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: applicationTool Context triple: [Fit Me loose finishing powder, applicationTool, powder brush]
-
A.
applicationRequirement
Indicates that one entity specifies a condition or prerequisite that must be met for the use, approval, or execution of another entity or process.
-
B.
applicationRange
Indicates the scope or extent within which something (such as a rule, function, or process) is validly applied or operates.
-
C.
aplicación
Indicates that one entity is the use or implementation of another entity for a specific purpose or function.
-
D.
exampleApplication
Indicates that something serves as a representative or illustrative instance of how an application is used or functions.
-
E.
applicationInterface
Indicates that one entity serves as an interface or interaction layer through which another entity accesses or uses an application’s functionality.
- F. None of above. chosen
Provenance (4 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_69e295463f7c8190b1c19dbd114641b9 |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f1d38f8a208190a293c64b9c9202c0 |
completed | April 29, 2026, 9:46 a.m. |
| PD | Predicate disambiguation | batch_69f1615994c48190a5de95d3f7e5cd0a |
completed | April 29, 2026, 1:39 a.m. |
| PDg | Predicate description generation | batch_69f16e35944c8190b57cfa31f1e9da1b |
completed | April 29, 2026, 2:34 a.m. |
Created at: April 17, 2026, 9:38 p.m.