Triple
T14116658
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Always |
E339791
|
entity |
| Predicate | competitor |
P1375
|
FINISHED |
| Object | Kotex |
E726040
|
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: Kotex | Statement: [Always, competitor, Kotex]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kotex Context triple: [Always, competitor, Kotex]
-
A.
Kotex
chosen
Kotex is a well-known feminine hygiene brand offering products such as sanitary pads, tampons, and liners.
-
B.
Sheex
Sheex is a performance bedding company known for its athletic-inspired, moisture-wicking sheets and sleepwear.
-
C.
Kleenex
Kleenex is a widely recognized brand of facial tissues and related paper products known for being a generic term for disposable tissues.
-
D.
Charmin
Charmin is a popular brand of toilet paper known for its softness and comfort, produced by Procter & Gamble.
-
E.
Wacoal
Wacoal is a Japanese company best known as a leading manufacturer and retailer of women's lingerie and intimate apparel.
- 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.