Triple
T13358787
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert Knight |
E318766
|
entity |
| Predicate | hasBrand |
P1500
|
FINISHED |
| Object | Fruit of the Loom |
E79839
|
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: Fruit of the Loom | Statement: [Robert Knight, hasBrand, Fruit of the Loom]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fruit of the Loom Context triple: [Robert Knight, hasBrand, Fruit of the Loom]
-
A.
Fruit of the Loom
chosen
Fruit of the Loom is a major American clothing manufacturer best known for its underwear, casualwear, and iconic fruit-themed logo.
-
B.
Hanesbrands
Hanesbrands is a leading American apparel company best known for its Hanes and Champion brands of underwear, activewear, and basic clothing.
-
C.
Old Navy
Old Navy is an American clothing and accessories retail chain known for offering affordable, family-oriented casual apparel.
-
D.
Levi's
Levi's is an iconic American denim and apparel brand best known for pioneering blue jeans and casual wear worldwide.
-
E.
Burlington Industries, Inc.
Burlington Industries, Inc. was a major American textile manufacturing company known for producing a wide range of fabrics and apparel materials.
- 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_69d806b7bbac8190b85278c87fa7aff3 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69da62887e588190bd7241c720a112a2 |
completed | April 11, 2026, 3:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f72677b2a48190aad30f3ee6cacefb |
completed | May 3, 2026, 10:41 a.m. |
Created at: April 9, 2026, 9:32 p.m.