Triple
T11899083
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Golf Wang |
E283103
|
entity |
| Predicate | collaboratedWith |
P435
|
FINISHED |
| Object | Levi's |
E31749
|
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: Levi's | Statement: [Golf Wang, collaboratedWith, Levi's]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Levi's Context triple: [Golf Wang, collaboratedWith, Levi's]
-
A.
Levi's
chosen
Levi's is an iconic American denim and apparel brand best known for pioneering blue jeans and casual wear worldwide.
-
B.
Sasson Jeans
Sasson Jeans was a popular American denim and sportswear brand that gained prominence in the late 1970s and 1980s for its fashion-forward jeans and memorable advertising campaigns.
-
C.
Hilfiger Denim
Hilfiger Denim is a casual clothing line under the Tommy Hilfiger fashion label, focusing on youthful, denim-centered apparel with a classic American style.
-
D.
Lucky Brand
Lucky Brand is an American denim and casual apparel company best known for its vintage-inspired jeans and laid-back Southern California style.
-
E.
Old Navy
Old Navy is an American clothing and accessories retail chain known for offering affordable, family-oriented casual 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_69d6ab2a90b08190a4e818821cc93e6d |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8dd13cc10819089d8d5103e562924 |
completed | April 10, 2026, 11:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f4182f18c08190b22706b024d60dd7 |
completed | May 1, 2026, 3:04 a.m. |
Created at: April 8, 2026, 9:44 p.m.