Triple
T3623661
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alexa Vega |
E76784
|
entity |
| Predicate | hasSingingVoiceType |
P49604
|
FINISHED |
| Object | mezzo-soprano |
—
|
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: mezzo-soprano | Statement: [Alexa Vega, hasSingingVoiceType, mezzo-soprano]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSingingVoiceType Context triple: [Alexa Vega, hasSingingVoiceType, mezzo-soprano]
-
A.
hasVocals
Indicates that the subject includes or features vocal elements, such as singing or spoken voice, rather than being purely instrumental or non-vocal.
-
B.
hasVocalPerformanceBy
Indicates that a vocal performance in a work or recording is performed by a specified person or group.
-
C.
hasMusicFilm
Indicates a relationship where a subject is associated with or linked to a film that features or centers around music.
-
D.
sangSoundtrackFor
Indicates that one entity performed or recorded the soundtrack music for a work associated with another entity.
-
E.
isSoundFilm
Indicates that a film includes synchronized recorded sound as an integral part of its presentation, rather than being a silent film.
- F. None of above. chosen
Provenance (4 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_69ad85dae2fc81908d1ceadbc6af0089 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc2bc79008190abe6900adcbda8de |
completed | March 8, 2026, 6:41 p.m. |
| PD | Predicate disambiguation | batch_69adb8410a5881909c94818d7060b2b0 |
completed | March 8, 2026, 5:56 p.m. |
| PDg | Predicate description generation | batch_69adb902e61c81908f10494f828e260f |
completed | March 8, 2026, 5:59 p.m. |
Created at: March 8, 2026, 3:23 p.m.