Triple
T14116396
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Downy |
E339786
|
entity |
| Predicate | hasProductLine |
P3585
|
FINISHED |
| Object | Downy Nature Blends |
E339786
|
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: Downy Nature Blends | Statement: [Downy, hasProductLine, Downy Nature Blends]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Downy Nature Blends Context triple: [Downy, hasProductLine, Downy Nature Blends]
-
A.
Downy
chosen
Downy is a popular fabric softener and laundry care brand known for its long-lasting freshness and fabric-conditioning products.
-
B.
Breeda Wool
Breeda Wool is an American actress known for her roles in television dramas and thrillers, including a prominent part in the series "Mr. Mercedes."
-
C.
Dot Cotton
Dot Cotton is a long-running, iconic character from the British soap opera EastEnders, known for her devout Christian faith, chain-smoking habit, and moral yet often troubled presence in Albert Square.
-
D.
Seaborn Cotton
Seaborn Cotton was a 17th-century New England Puritan minister and the son of prominent theologian John Cotton.
-
E.
Cotton Tufts
Cotton Tufts was an 18th-century American physician and patriot from Massachusetts who was active in public affairs during the Revolutionary era.
- 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.