Triple
T17990524
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Green Butchers |
E430356
|
entity |
| Predicate | featuresTone |
P45646
|
FINISHED |
| Object | macabre |
—
|
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: macabre | Statement: [The Green Butchers, featuresTone, macabre]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresTone Context triple: [The Green Butchers, featuresTone, macabre]
-
A.
supportsTone
Indicates that one entity is compatible with, enables, or can correctly handle a specified tone or tonal characteristic of another entity.
-
B.
featuresRhythm
Indicates that something includes, exhibits, or is characterized by a particular rhythmic pattern or structure.
-
C.
featuresVocalPercussion
Indicates that the subject includes or makes use of vocal percussion (such as beatboxing or mouth-made rhythmic sounds) as part of its content or performance.
-
D.
speakerFeatures
Indicates that certain characteristics, attributes, or properties are associated with a speaker in a given context.
-
E.
tonalCharacteristic
chosen
Indicates the specific quality or character of a sound’s tone, such as its color, texture, or expressive nuance, in relation to an 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_69d8b90364248190a37381adea932f42 |
completed | April 10, 2026, 8:46 a.m. |
| NER | Named-entity recognition | batch_69e4b29f127c81908b0c4cb3787e002c |
completed | April 19, 2026, 10:46 a.m. |
| PD | Predicate disambiguation | batch_69e3f90039e4819080527f860dca042e |
completed | April 18, 2026, 9:34 p.m. |
Created at: April 10, 2026, 10:23 a.m.