Triple
T32721421
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Isabel Marant |
E836682
|
entity |
| Predicate | diffusionLineFocus |
P174840
|
FINISHED |
| Object | casual ready-to-wear |
—
|
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: casual ready-to-wear | Statement: [Isabel Marant, diffusionLineFocus, casual ready-to-wear]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: diffusionLineFocus Context triple: [Isabel Marant, diffusionLineFocus, casual ready-to-wear]
-
A.
Flowline
Indicates a directed path or channel along which something (such as fluid, energy, or information) moves or is transmitted from one point to another.
-
B.
focusesLight
Indicates that one entity concentrates or directs light onto a specific area, object, or target.
-
C.
fieldLineEffect
Indicates the influence or impact that a field line exerts on another entity or system.
-
D.
differenceInFocus
Indicates that two related items vary specifically in their emphasis, attention, or focal point rather than in their core content or identity.
-
E.
connectedLine
Indicates that two entities are joined by a continuous line or linear connection.
- 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_69f34935455881909088975d79460418 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6c8b3c64881908faa5c22e5785dc8 |
completed | May 3, 2026, 4:01 a.m. |
| PD | Predicate disambiguation | batch_69f6c3f617c08190a70ba880210f908c |
completed | May 3, 2026, 3:41 a.m. |
| PDg | Predicate description generation | batch_69f6c77500a08190b2bdeca33bd2ac08 |
completed | May 3, 2026, 3:56 a.m. |
Created at: May 1, 2026, 1:11 a.m.