Triple
T17078469
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scott toilet paper |
E414409
|
entity |
| Predicate | competesWith |
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: [Scott toilet paper, competesWith, Cottonelle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cottonelle Context triple: [Scott toilet paper, competesWith, 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.
Tampax
Tampax is a leading global brand of feminine hygiene products, best known for its tampons.
- 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_69d886cef44c8190ba56c44b4e863e64 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dbe0e9cc8190b6c4b6065b474d1d |
completed | April 18, 2026, 7:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a012ee243c081909aa6d470e002222a |
completed | May 11, 2026, 1:20 a.m. |
Created at: April 10, 2026, 5:34 a.m.