Triple
T36778221
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Options |
E908690
|
entity |
| Predicate | featuresMaleGuestVocal |
P156097
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Options, featuresMaleGuestVocal, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresMaleGuestVocal Context triple: [Options, featuresMaleGuestVocal, true]
-
A.
vocalGender
Indicates the perceived or assigned gender associated with an entity’s voice in a vocal performance or recording.
-
B.
voiceType
Indicates the specific vocal style, quality, or role associated with an entity’s voice in a given context.
-
C.
featuresVocalStyleOf
Indicates that one entity exhibits or incorporates the distinctive vocal style or vocal characteristics associated with another entity.
-
D.
featuresVocal
Indicates that one entity includes or presents the vocal performance or voice of another entity.
-
E.
voiceActorMale
chosen
Indicates that the subject is a male voice actor who provides the voice for the associated character or role.
- 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_69f76e798aa08190ace31098d1b13e9f |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037c8e2c648190a65fc9c7872861af |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0e039481908a4a2666f76c5363 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:12 p.m.