Triple
T38100033
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bluegrass Hits |
E951350
|
entity |
| Predicate | includesVocalHarmony |
P83531
|
FINISHED |
| Object | high tenor lead |
—
|
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: high tenor lead | Statement: [Bluegrass Hits, includesVocalHarmony, high tenor lead]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesVocalHarmony Context triple: [Bluegrass Hits, includesVocalHarmony, high tenor lead]
-
A.
containsVocalHarmonies
chosen
Indicates that the subject includes multiple vocal parts sung together in harmony.
-
B.
hasAdditionalVocalElements
Indicates that an entity includes extra vocal components or embellishments beyond its primary or standard vocal parts.
-
C.
hasVocals
Indicates that the subject includes or features vocal elements, such as singing or spoken voice, rather than being purely instrumental or non-vocal.
-
D.
vocalHarmonyType
Indicates the specific kind or style of vocal harmony relationship that exists between the involved vocal parts or voices.
-
E.
includesScratchVocalsFrom
Indicates that one audio recording or track contains scratch (temporary or demo) vocal parts taken from another recording or session.
- 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_69f76f04960c8190a83f14ae4c67f5bc |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a037df1223c8190a5d61e4f8e6fd613 |
completed | May 12, 2026, 7:22 p.m. |
| PD | Predicate disambiguation | batch_6a037a1ad6c48190bfe35d350c1b4751 |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:21 p.m.