Triple
T25290186
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kerium Anti-Hairloss Intensive Treatment |
E634060
|
entity |
| Predicate | hasApplicationMode |
P96491
|
FINISHED |
| Object | leave-on treatment |
—
|
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: leave-on treatment | Statement: [Kerium Anti-Hairloss Intensive Treatment, hasApplicationMode, leave-on treatment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApplicationMode Context triple: [Kerium Anti-Hairloss Intensive Treatment, hasApplicationMode, leave-on treatment]
-
A.
hasApplicationType
chosen
Indicates that an entity is associated with or classified by a specific type or category of application.
-
B.
hasModeSystem
Indicates that one entity operates under, or is associated with, a particular mode defined or managed by another system.
-
C.
hasApp
Indicates that an entity possesses, provides, or is associated with a particular application.
-
D.
hasModernApplication
Indicates that something is currently used or applicable in modern contexts, practices, or technologies.
-
E.
hasWorkingMode
Indicates that an entity operates under or supports a particular mode or configuration of functioning.
- 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_69e75a9503d48190b80a005c6af0cb50 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f60c3b09488190ade1b69ff7f0df0e |
completed | May 2, 2026, 2:37 p.m. |
| PD | Predicate disambiguation | batch_69f60b8461ac81908c5bd3d73eed59f4 |
completed | May 2, 2026, 2:34 p.m. |
Created at: April 21, 2026, 1:21 p.m.