Triple
T37792691
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SMCLs |
E942125
|
entity |
| Predicate | appliesToContaminantType |
P1129
|
FINISHED |
| Object | aesthetic contaminants |
—
|
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: aesthetic contaminants | Statement: [SMCLs, appliesToContaminantType, aesthetic contaminants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appliesToContaminantType Context triple: [SMCLs, appliesToContaminantType, aesthetic contaminants]
-
A.
containsContaminant
Indicates that one entity includes, holds, or is tainted by an unwanted or harmful contaminating substance or element.
-
B.
appliesTo
chosen
Indicates that something is relevant, valid, or has effect in relation to a particular entity, case, or context.
-
C.
appliesToTypeOfUnit
Indicates that something is relevant or applicable specifically to a particular type or category of unit.
-
D.
appliesToProductType
Indicates that something (such as a rule, offer, or condition) is relevant or applicable specifically to a certain type or category of product.
-
E.
appliesAlsoTo
Indicates that a condition, rule, or characteristic that applies to one entity is additionally applicable to another 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_69f76ee6f1f4819091e2cf9c9e6aee19 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69ffbf84f4948190b41a7bba07ae61ec |
completed | May 9, 2026, 11:13 p.m. |
| PD | Predicate disambiguation | batch_69ffbf0a59f88190870dbe25d8a63a00 |
completed | May 9, 2026, 11:11 p.m. |
Created at: May 3, 2026, 4:19 p.m.