Triple
T1292657
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matrix |
E27580
|
entity |
| Predicate | notableProductType |
P28339
|
FINISHED |
| Object | permanent hair color |
—
|
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: permanent hair color | Statement: [Matrix, notableProductType, permanent hair color]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableProductType Context triple: [Matrix, notableProductType, permanent hair color]
-
A.
notableProduct
Indicates that a product is especially significant, prominent, or well-known in relation to the associated entity.
-
B.
notableProjectType
Indicates the type or category of a project for which an entity is particularly well-known or notable.
-
C.
notableTypeOfWork
Indicates that a work is a significant or defining example within a particular type or category of work associated with an entity.
-
D.
notableServiceType
Indicates that the subject is associated with a particular type or category of service that is especially notable or significant.
-
E.
notableCategory
Indicates that an entity is recognized as notable or significant within a particular category or classification.
- 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_69a496d4ec448190ad653b2590c46711 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c3bb3a9c81909db2ad91defd87b6 |
completed | March 1, 2026, 10:54 p.m. |
| PD | Predicate disambiguation | batch_69a4bee64d908190b6a9bb479959d523 |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4c3b9ebdc819098de4d3288201bc1 |
completed | March 1, 2026, 10:54 p.m. |
Created at: March 1, 2026, 7:51 p.m.