Triple
T6102202
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blow Up the Outside World |
E136022
|
entity |
| Predicate | hasIntrospectiveLyrics |
P4921
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Blow Up the Outside World, hasIntrospectiveLyrics, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasIntrospectiveLyrics Context triple: [Blow Up the Outside World, hasIntrospectiveLyrics, true]
-
A.
hasLyric
Indicates that one entity (typically a musical work or track) contains or is associated with the lyrics provided by another entity.
-
B.
hasExplicitLyrics
Indicates that the referenced content contains explicit language or themes, such as profanity, sexual content, or strong violence.
-
C.
hasPoeticLyrics
Indicates that something (such as a song, text, or speech) contains lyrics or wording that are artistic, expressive, or characteristic of poetry.
-
D.
hasLyricalTheme
chosen
Indicates that one entity (typically a creative work) features or is characterized by a particular lyrical subject, topic, or theme.
-
E.
hasLyricalForm
Indicates that one entity (typically a musical or poetic work) possesses or is characterized by a particular lyrical structure or form.
- 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_69c0087dee9881909e3655be88208c01 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c05b3c073c81908248c799934d6fce |
completed | March 22, 2026, 9:12 p.m. |
| PD | Predicate disambiguation | batch_69c049f5ac988190b62ba565153aaa35 |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:13 p.m.