Triple
T8334031
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kimberly-Clark Corporation |
E195142
|
entity |
| Predicate | brand |
P1500
|
FINISHED |
| Object |
Kleenex
Kleenex is a widely recognized brand of facial tissues and related paper products known for being a generic term for disposable tissues.
|
E726038
|
NE FINISHED |
How this triple was built (4 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: Kleenex | Statement: [Kimberly-Clark Corporation, brand, Kleenex]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kleenex Context triple: [Kimberly-Clark Corporation, brand, Kleenex]
-
A.
Blistex
Blistex is an American company best known for producing lip care and other medicated skin care products.
-
B.
Charmin
Charmin is a popular brand of toilet paper known for its softness and comfort, produced by Procter & Gamble.
-
C.
Lifebuoy
Lifebuoy is a long-established global soap and hygiene brand known for its antibacterial products and health-focused marketing.
-
D.
Brawny
Brawny is a popular American paper towel brand known for its strong, absorbent products and its iconic lumberjack-themed packaging.
-
E.
Suavitel
Suavitel is a popular fabric softener brand known for its long-lasting fragrances and softening properties, marketed primarily in Latin American and U.S. Hispanic households.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Kleenex Triple: [Kimberly-Clark Corporation, brand, Kleenex]
Generated description
Kleenex is a widely recognized brand of facial tissues and related paper products known for being a generic term for disposable tissues.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kleenex Target entity description: Kleenex is a widely recognized brand of facial tissues and related paper products known for being a generic term for disposable tissues.
-
A.
Blistex
Blistex is an American company best known for producing lip care and other medicated skin care products.
-
B.
Charmin
Charmin is a popular brand of toilet paper known for its softness and comfort, produced by Procter & Gamble.
-
C.
Lifebuoy
Lifebuoy is a long-established global soap and hygiene brand known for its antibacterial products and health-focused marketing.
-
D.
Brawny
Brawny is a popular American paper towel brand known for its strong, absorbent products and its iconic lumberjack-themed packaging.
-
E.
Suavitel
Suavitel is a popular fabric softener brand known for its long-lasting fragrances and softening properties, marketed primarily in Latin American and U.S. Hispanic households.
- F. None of above. chosen
Provenance (5 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_69ca82e87f2c8190bdb71ee29dfc642d |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7fbe61f481909cde8ab2c42f89fc |
completed | March 31, 2026, 8:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cd95d19178819090815692e847c4e0 |
completed | April 1, 2026, 10:01 p.m. |
| NEDg | Description generation | batch_69cdab61d00c81909ce2c0d718a2dc1a |
completed | April 1, 2026, 11:33 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cdb2ef889c8190af6efb9473f8804c |
completed | April 2, 2026, 12:06 a.m. |
Created at: March 30, 2026, 5:57 p.m.