Triple
T26989093
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Choupette |
E679816
|
entity |
| Predicate | describedByKarlLagerfeldAs |
P169929
|
FINISHED |
| Object | famous |
—
|
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: famous | Statement: [Choupette, describedByKarlLagerfeldAs, famous]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: describedByKarlLagerfeldAs Context triple: [Choupette, describedByKarlLagerfeldAs, famous]
-
A.
personHasNotableStyle
Indicates that a person is recognized for having a distinctive or noteworthy style.
-
B.
inTheStyleOf
Indicates that one entity is created, performed, or presented in a manner that imitates or closely resembles the characteristic style of another entity.
-
C.
fashionCharacteristic
Indicates a relationship where one entity possesses or exhibits a particular style, trend, or fashion-related attribute in relation to another.
-
D.
introducedByFashionHouse
Indicates that a fashion item, collection, or trend was first launched or brought to market by a specific fashion house.
-
E.
fashionLabelSpecialty
Indicates that a fashion label is particularly focused on, known for, or specialized in a specific type of product, style, or design niche.
- F. None of above. chosen
Provenance (4 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_69eeeb5138ac8190b3c273ddc659a54f |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f688d015908190ad5df37030ecf332 |
completed | May 2, 2026, 11:29 p.m. |
| PD | Predicate disambiguation | batch_69f68609c0b08190a8e1238a4d97c270 |
completed | May 2, 2026, 11:17 p.m. |
| PDg | Predicate description generation | batch_69f688034580819086a0f9100645f8ba |
completed | May 2, 2026, 11:25 p.m. |
Created at: April 27, 2026, 6:50 a.m.