Triple
T12326476
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manon Lescaut |
E293841
|
entity |
| Predicate | GeronteVoiceType |
P2000
|
FINISHED |
| Object | bass |
—
|
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: bass | Statement: [Manon Lescaut, GeronteVoiceType, bass]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: GeronteVoiceType Context triple: [Manon Lescaut, GeronteVoiceType, bass]
-
A.
voiceType
chosen
Indicates the specific vocal style, quality, or role associated with an entity’s voice in a given context.
-
B.
voiceAppearance
Indicates that one entity’s voice is present, heard, or featured in association with another entity (such as a work, scene, or medium).
-
C.
vocalGender
Indicates the perceived or assigned gender associated with an entity’s voice in a vocal performance or recording.
-
D.
speakerType
Indicates the role or category of a participant in a communicative act (e.g., narrator, quoted speaker, system voice) within a given context.
-
E.
voiceActingType
Indicates the specific style or category of voice performance used in an audio-visual work or production.
- 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_69d6ab6ae0dc8190b1522a9c1c55c114 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f621570819091ee1db2609233ea |
completed | April 10, 2026, 6:20 p.m. |
| PD | Predicate disambiguation | batch_69d93ec5be788190b82d2edc6a0f1095 |
completed | April 10, 2026, 6:17 p.m. |
Created at: April 8, 2026, 9:53 p.m.