Triple
T35866200
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tupperware Brands |
E1037093
|
entity |
| Predicate | hasNotableProductFeature |
P642
|
FINISHED |
| Object | airtight seals |
—
|
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: airtight seals | Statement: [Tupperware Brands, hasNotableProductFeature, airtight seals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableProductFeature Context triple: [Tupperware Brands, hasNotableProductFeature, airtight seals]
-
A.
hasNotableFeature
chosen
Indicates that an entity possesses a specific characteristic, trait, or attribute that is considered significant or noteworthy.
-
B.
hasNotableInnovation
Indicates that an entity is associated with a significant, distinguishing innovation or breakthrough.
-
C.
hasNotableFoodProduct
Indicates that an entity is associated with a food product that is recognized as notable, distinctive, or significant.
-
D.
hasNotableUseExample
Indicates that there exists a particularly significant or illustrative example of how something is used.
-
E.
hasSideFeature
Indicates that an entity possesses a specific secondary or auxiliary feature on its side or lateral aspect.
- 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_69f76e1d279c8190843e5b64a0a12c3f |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037ce70f54819082946dad8d380825 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a069e6c8190857b611fffb7b867 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:06 p.m.