Triple
T15436770
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Texas Chainsaw Massacre (2003) score |
E369783
|
entity |
| Predicate | soundPalette |
P84027
|
FINISHED |
| Object | distorted metallic sounds |
—
|
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: distorted metallic sounds | Statement: [The Texas Chainsaw Massacre (2003) score, soundPalette, distorted metallic sounds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: soundPalette Context triple: [The Texas Chainsaw Massacre (2003) score, soundPalette, distorted metallic sounds]
-
A.
soundMotif
Indicates a recurring or thematically significant sound pattern associated with an entity, event, or context.
-
B.
soundCategory
chosen
Indicates the classification relationship where a sound is assigned to a particular category or type of sound.
-
C.
soundEngine
Indicates that one entity functions as or provides the sound engine (audio processing or synthesis system) used by another entity.
-
D.
soundDesignBy
Indicates that the sound design for a work (such as a film, game, or performance) is created or supervised by a particular person or entity.
-
E.
soundChip
Indicates that one entity functions as or contains the sound-processing chip used by 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_69d85a19180081909925012fbf4e62a3 |
completed | April 10, 2026, 2:02 a.m. |
| NER | Named-entity recognition | batch_69e03edca064819081510bf303271062 |
completed | April 16, 2026, 1:43 a.m. |
| PD | Predicate disambiguation | batch_69ded28276f481908c2038bb301e57cf |
completed | April 14, 2026, 11:49 p.m. |
Created at: April 10, 2026, 3:21 a.m.