Triple
T1665376
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Woman with a Parasol |
E35997
|
entity |
| Predicate | lightingCharacteristic |
P30545
|
FINISHED |
| Object | backlighting |
—
|
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: backlighting | Statement: [Woman with a Parasol, lightingCharacteristic, backlighting]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lightingCharacteristic Context triple: [Woman with a Parasol, lightingCharacteristic, backlighting]
-
A.
lightingColor
Indicates the color or hue of the lighting applied to or associated with an entity.
-
B.
hasLighting
Indicates that one entity is equipped with, contains, or is characterized by a particular type or configuration of lighting.
-
C.
designLuminosity
Indicates the specified luminosity level or brightness characteristics that something is designed or intended to have.
-
D.
lightSourceFor
Indicates that one entity serves as the source of illumination for another entity.
-
E.
lightRange
Indicates the distance or area over which a light source effectively emits or illuminates.
- 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_69a8861286808190939afff3ce8ee31e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa994f92b0819084ee2f6a672334b9 |
completed | March 6, 2026, 9:07 a.m. |
| PD | Predicate disambiguation | batch_69a907d2475c8190b7ec7dccd3335eb1 |
completed | March 5, 2026, 4:34 a.m. |
| PDg | Predicate description generation | batch_69a94192abc0819092fc00fef9d53bcb |
completed | March 5, 2026, 8:40 a.m. |
Created at: March 4, 2026, 7:29 p.m.