Triple
T30933581
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kevin's Famous Chili |
E788058
|
entity |
| Predicate | sceneTone |
P170819
|
FINISHED |
| Object | comic disaster |
—
|
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: comic disaster | Statement: [Kevin's Famous Chili, sceneTone, comic disaster]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sceneTone Context triple: [Kevin's Famous Chili, sceneTone, comic disaster]
-
A.
brightnessVariation
Indicates a change or fluctuation in the level of brightness of an entity over time or across conditions.
-
B.
visualTone
Indicates how the visual style, mood, or aesthetic quality of one entity relates to or affects another.
-
C.
textureContrast
Indicates a relationship where two surfaces or regions differ noticeably in their tactile or visual texture qualities.
-
D.
brightnessCorrelatesWith
Indicates that changes in the brightness of one entity are systematically associated with changes in the brightness of another entity.
-
E.
rayBrightness
Indicates the intensity or luminance level associated with a specific ray.
- 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_69f224c0b7fc819090cb89df60d23653 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f695f9fe7c819084322bf6cdc70a13 |
completed | May 3, 2026, 12:25 a.m. |
| PD | Predicate disambiguation | batch_69f690ed5d008190831cf8e44cce28af |
completed | May 3, 2026, 12:03 a.m. |
| PDg | Predicate description generation | batch_69f695385a2881908cc28ef97fffc867 |
completed | May 3, 2026, 12:22 a.m. |
Created at: April 29, 2026, 8:52 p.m.