Triple
T25003969
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kerium DS Anti-Dandruff Shampoo |
E625789
|
entity |
| Predicate | usageRoute |
P157534
|
FINISHED |
| Object | topical application to wet hair |
—
|
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: topical application to wet hair | Statement: [Kerium DS Anti-Dandruff Shampoo, usageRoute, topical application to wet hair]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usageRoute Context triple: [Kerium DS Anti-Dandruff Shampoo, usageRoute, topical application to wet hair]
-
A.
usedRoutes
Indicates that an entity has utilized or traveled along specific routes.
-
B.
routePurpose
Indicates the intended function or goal that a particular route is designed or used to serve.
-
C.
routeOf
Indicates that one entity is the path, course, or trajectory taken or followed by another entity (such as a vehicle, shipment, or signal).
-
D.
currentUseOfRoute
Indicates that a particular route is presently being used for a specific purpose, activity, or traffic flow.
-
E.
routeChoiceIn
Indicates that a particular route is selected or used within a given route choice or decision context.
- 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_69e2ff26c50481908bc82e799c9e6587 |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f44b0ee0388190a07b6c0bcd817af9 |
completed | May 1, 2026, 6:41 a.m. |
| PD | Predicate disambiguation | batch_69f442c0c2e88190acd7f170f10ccef6 |
completed | May 1, 2026, 6:05 a.m. |
| PDg | Predicate description generation | batch_69f448fe11f08190bdd53ca7ba2d51e4 |
completed | May 1, 2026, 6:32 a.m. |
Created at: April 18, 2026, 6:05 a.m.