Triple
T23001785
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Blacksmith’s Shop |
E572649
|
entity |
| Predicate | lightingContrast |
P76521
|
FINISHED |
| Object | strong contrast between light and shadow |
—
|
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: strong contrast between light and shadow | Statement: [The Blacksmith’s Shop, lightingContrast, strong contrast between light and shadow]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lightingContrast Context triple: [The Blacksmith’s Shop, lightingContrast, strong contrast between light and shadow]
-
A.
brightnessVariation
Indicates a change or fluctuation in the level of brightness of an entity over time or across conditions.
-
B.
achievesContrast
chosen
Indicates that one entity creates or enhances a visual or conceptual difference relative to another entity.
-
C.
textureContrast
Indicates a relationship where two surfaces or regions differ noticeably in their tactile or visual texture qualities.
-
D.
albedoContrast
Indicates the degree to which two surfaces or regions differ in their reflectivity (albedo), typically highlighting contrast in brightness.
-
E.
themeContrast
Indicates a relationship where two themes are compared or opposed to highlight their differences or tension.
- 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_69e245b6a3ac81908087599eefe3e365 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f18353d05481909abacb48a14ef21e |
completed | April 29, 2026, 4:04 a.m. |
| PD | Predicate disambiguation | batch_69ef3b9cd5488190bcd23183179f48cd |
completed | April 27, 2026, 10:34 a.m. |
Created at: April 17, 2026, 3:50 p.m.