Triple
T13069323
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | He Loves Me (Lyzel in E Flat) |
E329411
|
entity |
| Predicate | hasVocalCharacteristics |
P29850
|
FINISHED |
| Object | vocal acrobatics |
—
|
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: vocal acrobatics | Statement: [He Loves Me (Lyzel in E Flat), hasVocalCharacteristics, vocal acrobatics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVocalCharacteristics Context triple: [He Loves Me (Lyzel in E Flat), hasVocalCharacteristics, vocal acrobatics]
-
A.
vocalizationCharacteristic
chosen
Indicates how an entity’s vocal sounds are characterized, such as their quality, style, or distinctive acoustic features.
-
B.
hasVocalForces
Indicates that an entity involves or employs vocal performers or vocal parts as a contributing force.
-
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.
hasNotableVocalType
Indicates that an entity is associated with a specific, noteworthy type or quality of vocalization or voice.
-
E.
hasVocalStyleComparedTo
Indicates a comparison between entities based on the similarity or resemblance of their vocal style.
- 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_69d80771749c81909a6d9197b9504872 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d980ec8ba48190baf52c7823482680 |
completed | April 10, 2026, 10:59 p.m. |
| PD | Predicate disambiguation | batch_69d9803d46688190bac6b7d208f08d01 |
completed | April 10, 2026, 10:57 p.m. |
Created at: April 9, 2026, 9 p.m.