Triple
T31504899
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Super Viernes |
E803789
|
entity |
| Predicate | usesLightingEffects |
P69537
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Super Viernes, usesLightingEffects, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesLightingEffects Context triple: [Super Viernes, usesLightingEffects, yes]
-
A.
hasLightingEffect
chosen
Indicates that one entity applies, produces, or is associated with a particular lighting effect on another entity or environment.
-
B.
usesLightingFor
Indicates that one entity employs or relies on a particular lighting setup, technology, or condition to achieve a purpose or perform an action.
-
C.
hasLighting
Indicates that one entity is equipped with, contains, or is characterized by a particular type or configuration of lighting.
-
D.
hasLightingImprovements
Indicates that an entity has enhancements or upgrades made to its lighting conditions or systems.
-
E.
portraysLighting
Indicates that one entity visually represents or depicts the lighting conditions or illumination effects of another entity.
- 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_69f348cae52081909fa8e5f697523ae3 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6d16f5cb881908eed141afaaa0b51 |
completed | May 3, 2026, 4:39 a.m. |
| PD | Predicate disambiguation | batch_69f6cfe45554819089cbbd538d992132 |
completed | May 3, 2026, 4:32 a.m. |
Created at: April 30, 2026, 9:46 p.m.