Triple
T12976436
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beetlejuice (film score) |
E321536
|
entity |
| Predicate | basedOnToneOf |
P49759
|
FINISHED |
| Object | supernatural comedy |
—
|
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: supernatural comedy | Statement: [Beetlejuice (film score), basedOnToneOf, supernatural comedy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: basedOnToneOf Context triple: [Beetlejuice (film score), basedOnToneOf, supernatural comedy]
-
A.
contributesToTone
chosen
Indicates that one entity plays a role in shaping, influencing, or determining the overall tone or mood of another entity.
-
B.
inTonality
Indicates that something (such as a musical element, passage, or piece) is expressed, structured, or interpreted within a specific musical key or tonal framework.
-
C.
isToneNeutral
Indicates that the tone of the referenced content is neither positive nor negative, but emotionally neutral or unbiased.
-
D.
tone
Indicates the characteristic attitude or emotional quality expressed in how something is communicated or presented.
-
E.
basedOnText
Indicates that something is derived, adapted, or developed from a specific text source.
- 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_69d80763bd6c819094437da5b20b01d2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97f2a71a0819098bb6cf8a4b2208a |
completed | April 10, 2026, 10:52 p.m. |
| PD | Predicate disambiguation | batch_69d97dbdd94c8190ac4bbecca02dc77b |
completed | April 10, 2026, 10:46 p.m. |
Created at: April 9, 2026, 8:37 p.m.