Triple
T22836666
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Next plc |
E565966
|
entity |
| Predicate | hasBrand |
P1500
|
FINISHED |
| Object | Lipsy |
—
|
NE NERFINISHED |
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: Lipsy | Statement: [Next plc, hasBrand, Lipsy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lipsy Context triple: [Next plc, hasBrand, Lipsy]
-
A.
Lipsy
chosen
Lipsy is a British fashion brand known for its trend-led womenswear and party dresses, owned by the retail company Next plc.
-
B.
Red Lips
"Red Lips" is a 2012 electropop/grunge-influenced single by American singer Sky Ferreira, known for its abrasive sound and collaboration with producer Greg Kurstin.
-
C.
Cookie Lips
"Cookie Lips" is a song by the indie rock supergroup Nice As Fuck, known for its minimalist style and politically tinged, lo-fi sound.
-
D.
Sugar Lips
"Sugar Lips" is a popular jazz trumpet tune by Al Hirt that became one of his signature hits in the 1960s.
-
E.
Hot Lips
Hot Lips is the nickname of Oran "Hot Lips" Page, an influential American jazz trumpeter and vocalist known for his powerful playing and contributions to the swing era.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e245869e188190a196584f36e682da |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17e2f09608190bc8e465e53b39e2e |
completed | April 29, 2026, 3:42 a.m. |
Created at: April 17, 2026, 3:35 p.m.