Triple
T20578905
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Every Kind of Mood – Randy, Randi, Randee |
E505300
|
entity |
| Predicate | featuresMoodRange |
P62080
|
FINISHED |
| Object | varied emotional styles |
—
|
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: varied emotional styles | Statement: [Every Kind of Mood – Randy, Randi, Randee, featuresMoodRange, varied emotional styles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresMoodRange Context triple: [Every Kind of Mood – Randy, Randi, Randee, featuresMoodRange, varied emotional styles]
-
A.
featuresMood
chosen
Indicates that something includes, presents, or conveys a particular mood or emotional atmosphere.
-
B.
hasMood
Indicates that an entity is experiencing or characterized by a particular emotional or affective state.
-
C.
supportsMood
Indicates that one entity helps maintain, enhance, or positively influence the emotional state or mood of another entity.
-
D.
hasMoodSystem
Indicates that an entity possesses or is associated with a system responsible for managing or representing moods or emotional states.
-
E.
depictsMood
Indicates that one entity visually represents or conveys the emotional state or mood 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_69e0b4b721588190993ac7b0a9be2736 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a90cc22c8190969e3a21ae92f1c9 |
completed | April 20, 2026, 10:30 p.m. |
| PD | Predicate disambiguation | batch_69e59fffe1748190825e4eaa90340631 |
completed | April 20, 2026, 3:39 a.m. |
Created at: April 16, 2026, 11:39 a.m.