Triple
T33950552
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maison Margiela |
E870425
|
entity |
| Predicate | usesDesignMotif |
P162950
|
FINISHED |
| Object | visible construction details |
—
|
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: visible construction details | Statement: [Maison Margiela, usesDesignMotif, visible construction details]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesDesignMotif Context triple: [Maison Margiela, usesDesignMotif, visible construction details]
-
A.
hasDesign
Indicates that one entity possesses, embodies, or is characterized by a particular design associated with another entity.
-
B.
usesDesignModel
Indicates that one entity applies or relies on a particular design model in performing its function or defining its structure.
-
C.
hasFlowerMotif
Indicates that one entity features or is decorated with a flower-themed design or pattern in relation to another entity.
-
D.
traditionalMotif
Indicates that something incorporates, represents, or is characterized by a motif rooted in established cultural or historical traditions.
-
E.
usedDesignFeature
chosen
Indicates that one entity employed or incorporated a particular design feature in its creation, implementation, or functionality.
- 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_69f3499c2d7481909c953a5010227725 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f70b966860819089cf92927f47c5f1 |
completed | May 3, 2026, 8:47 a.m. |
| PD | Predicate disambiguation | batch_69f70abe43e08190b2a30930d96247c1 |
completed | May 3, 2026, 8:43 a.m. |
Created at: May 1, 2026, 1:49 a.m.