Triple
T299504
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frauenliebe und -leben |
E6166
|
entity |
| Predicate | typicalVoiceType |
P2000
|
FINISHED |
| Object | female voice |
—
|
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: female voice | Statement: [Frauenliebe und -leben, typicalVoiceType, female voice]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalVoiceType Context triple: [Frauenliebe und -leben, typicalVoiceType, female voice]
-
A.
voiceType
chosen
Indicates the specific vocal style, quality, or role associated with an entity’s voice in a given context.
-
B.
typicalSpeaker
Indicates that the subject is a prototypical or characteristic speaker or source of utterances in the context of the object.
-
C.
vocalizationMethod
Indicates the manner or technique by which an entity produces a sound or vocal expression.
-
D.
spokenBy
Indicates that a particular utterance, statement, or piece of speech is produced or said by a specific entity.
-
E.
vocalRange
Indicates the span of pitches or notes that an entity (such as a singer or instrument) is capable of producing.
- 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_69a2e79114b081909490b3bf5a5dbb51 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2ea0dd1dc8190aecd5afdeb2fd74b |
completed | Feb. 28, 2026, 1:13 p.m. |
| PD | Predicate disambiguation | batch_69a2e9398df08190af40063a2de7a1d0 |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:06 p.m.