Triple
T5082307
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fashion Victim |
E114545
|
entity |
| Predicate | title |
P38
|
FINISHED |
| Object | Fashion Victim |
E114545
|
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: Fashion Victim | Statement: [Fashion Victim, title, Fashion Victim]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fashion Victim Context triple: [Fashion Victim, title, Fashion Victim]
-
A.
Fashion Victim
chosen
Fashion Victim is a 2008 British comedy film about a man whose obsession with designer clothes leads to crime and chaos.
-
B.
Fashion Police
Fashion Police is an American television series on the E! network that humorously critiques and comments on celebrity fashion and red carpet looks.
-
C.
Fashn
Fashn is a city in Egypt located within the Beni Suef Governorate along the Nile River.
-
D.
Lolita fashion
Lolita fashion is a Japanese street style characterized by Victorian- and Rococo-inspired dresses, petticoats, and elaborate, doll-like aesthetics.
-
E.
Fashion Avenue
Fashion Avenue is the nickname for Manhattan’s Seventh Avenue, a major New York City thoroughfare historically associated with the garment and fashion industry.
- 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_69bd443dbf908190a9401e9c2dc7bd7d |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd74fb3df4819082bd8ae64e207ceb |
completed | March 20, 2026, 4:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69beb135912c81909dd32d21b604e1b1 |
completed | March 21, 2026, 2:54 p.m. |
Created at: March 20, 2026, 1:39 p.m.