Triple
T13069169
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beautifully Human: Words and Sounds Vol. 2 |
E329407
|
entity |
| Predicate | featuresLyricsStyle |
P9652
|
FINISHED |
| Object | poetic lyrics |
—
|
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: poetic lyrics | Statement: [Beautifully Human: Words and Sounds Vol. 2, featuresLyricsStyle, poetic lyrics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresLyricsStyle Context triple: [Beautifully Human: Words and Sounds Vol. 2, featuresLyricsStyle, poetic lyrics]
-
A.
hasLyricalStyle
chosen
Indicates that one entity possesses or is characterized by a particular lyrical style in relation to another entity or context.
-
B.
lyricType
Indicates the specific category or role that a lyric plays within a musical or lyrical work (e.g., verse, chorus, bridge).
-
C.
featuresIntrospectiveLyrics
Indicates that the subject contains lyrics characterized by self-reflection, inner thought, or personal emotional examination.
-
D.
hasLyricsFeature
Indicates that something possesses a particular characteristic or attribute related to its lyrics.
-
E.
hasLyricsTone
Indicates the tonal quality or emotional character expressed by the lyrics of a piece of music.
- 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.