Triple
T23996234
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fit Me loose finishing powder |
E605195
|
entity |
| Predicate | hasApplicator |
P64701
|
FINISHED |
| Object | no built-in applicator |
—
|
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: no built-in applicator | Statement: [Fit Me loose finishing powder, hasApplicator, no built-in applicator]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApplicator Context triple: [Fit Me loose finishing powder, hasApplicator, no built-in applicator]
-
A.
applicatorType
chosen
Indicates the specific kind or method of applicator used to apply a substance or product in the described relationship.
-
B.
hasApp
Indicates that an entity possesses, provides, or is associated with a particular application.
-
C.
hasAppointer
Indicates that one entity is responsible for appointing or assigning another entity to a role, position, or function.
-
D.
appliesOver
Indicates that one entity’s effect, rule, or condition extends across or is valid for a specified range, domain, or set of entities.
-
E.
appliesVia
Indicates that an action, rule, or effect is carried out, implemented, or achieved through a specified method, medium, or mechanism.
- 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_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. |
Created at: April 17, 2026, 9:38 p.m.