Triple
T14646370
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | View of Arles with Irises in the Foreground |
E343860
|
entity |
| Predicate | foregroundSubject |
P107892
|
FINISHED |
| Object | irises |
—
|
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: irises | Statement: [View of Arles with Irises in the Foreground, foregroundSubject, irises]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: foregroundSubject Context triple: [View of Arles with Irises in the Foreground, foregroundSubject, irises]
-
A.
foregrounds
chosen
Indicates that one entity is brought into primary focus or prominence relative to others in a given context.
-
B.
formerFocus
Indicates that an entity previously served as the primary focus or main subject of attention, but no longer holds that status.
-
C.
primaryFront
Indicates that one entity serves as the main or most important front-facing side or surface in relation to another entity.
-
D.
front
Indicates that one entity is located directly before or facing another entity along a primary viewing or movement direction.
-
E.
frontOf
Indicates that one entity is positioned directly before another along a primary viewing or movement direction.
- 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_69d822e1a2cc81908e5bb93cf61ce3cc |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb4ebe8048190a2935d00c9cfd8be |
completed | April 14, 2026, 9:43 p.m. |
| PD | Predicate disambiguation | batch_69de657359c88190b082e3e9f86fc1d7 |
completed | April 14, 2026, 4:04 p.m. |
Created at: April 10, 2026, 1:26 a.m.