Triple
T14117073
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charmin |
E339799
|
entity |
| Predicate | competitor |
P1375
|
FINISHED |
| Object | Cottonelle |
E726039
|
NE 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: Cottonelle | Statement: [Charmin, competitor, Cottonelle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cottonelle Context triple: [Charmin, competitor, Cottonelle]
-
A.
Cottonelle
chosen
Cottonelle is a popular Kimberly-Clark brand of bathroom tissue and related personal care products known for its softness and comfort.
-
B.
Charmin
Charmin is a popular brand of toilet paper known for its softness and comfort, produced by Procter & Gamble.
-
C.
Brawny
Brawny is a popular American paper towel brand known for its strong, absorbent products and its iconic lumberjack-themed packaging.
-
D.
Kleenex
Kleenex is a widely recognized brand of facial tissues and related paper products known for being a generic term for disposable tissues.
-
E.
Irving Tissue
Irving Tissue is a North American manufacturer of tissue and paper products, known for producing household paper brands as part of the J.D. Irving group of companies.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d81c6a95b481909e39111e0c1f31ee |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de6010a03c81909f5f160f8d1fa8fa |
completed | April 14, 2026, 3:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcd0baa328819099511dfa7b9666d3 |
completed | May 7, 2026, 5:49 p.m. |
Created at: April 9, 2026, 10:22 p.m.