Triple
T14646379
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | View of Arles with Irises in the Foreground |
E343860
|
entity |
| Predicate | hasForeground |
P80461
|
FINISHED |
| Object | flower bed of 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: flower bed of irises | Statement: [View of Arles with Irises in the Foreground, hasForeground, flower bed of irises]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasForeground Context triple: [View of Arles with Irises in the Foreground, hasForeground, flower bed of irises]
-
A.
hasForegroundElement
chosen
Indicates that one element is positioned or perceived as being in the foreground relative to other elements in a scene or composition.
-
B.
hasBackground
Indicates that an entity possesses or is associated with a particular background, such as context, setting, or prior circumstances.
-
C.
hasBackgroundColor
Indicates that an entity possesses or is associated with a specific background color.
-
D.
hasFront
Indicates that an entity possesses or is associated with a front-facing side, surface, or portion.
-
E.
hasProgramFocus
Indicates that an entity (such as a program or initiative) is oriented around or primarily concerned with a particular thematic area, topic, or objective.
- 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.