Triple
T17340187
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lisa Fremont |
E421045
|
entity |
| Predicate | wardrobeNotedFor |
P36462
|
FINISHED |
| Object | high-fashion dresses |
—
|
LITERAL 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: high-fashion dresses | Statement: [Lisa Fremont, wardrobeNotedFor, high-fashion dresses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wardrobeNotedFor Context triple: [Lisa Fremont, wardrobeNotedFor, high-fashion dresses]
-
A.
wardrobeFeature
Indicates that a wardrobe possesses or includes a specific feature, attribute, or functional element.
-
B.
notableOutfit
chosen
Indicates that an entity is known for or associated with wearing a particular outfit or style of clothing.
-
C.
personHasNotableStyle
Indicates that a person is recognized for having a distinctive or noteworthy style.
-
D.
fashionCharacteristic
Indicates a relationship where one entity possesses or exhibits a particular style, trend, or fashion-related attribute in relation to another.
-
E.
fashionLabel
Indicates that an entity is a fashion brand or label associated with the design, production, or marketing of clothing or accessories.
- F. None of above.
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_69d889d3adc881909319f1edb8d2a956 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43a14ec90819098db2ac0d58a53e1 |
completed | April 19, 2026, 2:12 a.m. |
| PD | Predicate disambiguation | batch_69e3b021a5bc81909ae55406f9d0b37f |
completed | April 18, 2026, 4:24 p.m. |
Created at: April 10, 2026, 5:44 a.m.