Triple
T6533569
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Great Lash mascara |
E152289
|
entity |
| Predicate | brushType |
P64701
|
FINISHED |
| Object | traditional bristle 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: traditional bristle brush | Statement: [Great Lash mascara, brushType, traditional bristle brush]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: brushType Context triple: [Great Lash mascara, brushType, traditional bristle brush]
-
A.
usesBrushworkType
Indicates that an entity employs or is characterized by a particular type or style of brushwork in its creation or execution.
-
B.
bladeType
Indicates the specific kind or category of blade associated with an object or entity.
-
C.
applicatorType
chosen
Indicates the specific kind or method of applicator used to apply a substance or product in the described relationship.
-
D.
toolUsed
Indicates that an action or task is performed using a particular tool as the means or instrument.
-
E.
stickType
Indicates the specific kind or category of stick associated with or used in relation to an 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_69c688048ec8819093a47f7d332e12ec |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6adbf3a748190b0fb52122faaf6d3 |
completed | March 27, 2026, 4:18 p.m. |
| PD | Predicate disambiguation | batch_69c68abd9c7c819099e4fe8097cd1b28 |
completed | March 27, 2026, 1:48 p.m. |
Created at: March 27, 2026, 1:46 p.m.