Triple
T5054382
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | I Threw It All Away |
E113862
|
entity |
| Predicate | hasLyricSubject |
P7609
|
FINISHED |
| Object | reflection on a failed relationship |
—
|
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: reflection on a failed relationship | Statement: [I Threw It All Away, hasLyricSubject, reflection on a failed relationship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLyricSubject Context triple: [I Threw It All Away, hasLyricSubject, reflection on a failed relationship]
-
A.
hasLyric
Indicates that one entity (typically a musical work or track) contains or is associated with the lyrics provided by another entity.
-
B.
hasLyricsTheme
chosen
Indicates that the lyrics of a work primarily concern or revolve around a specified theme or subject.
-
C.
hasLyricalTheme
Indicates that one entity (typically a creative work) features or is characterized by a particular lyrical subject, topic, or theme.
-
D.
hasLyricCharacter
Indicates that a musical work or song includes a specific character or persona within its lyrics.
-
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_69bd443aa1f88190abb992d138f2cf42 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd744ccb888190a8a0ddd7c4d62f35 |
completed | March 20, 2026, 4:22 p.m. |
| PD | Predicate disambiguation | batch_69bd715479f08190933604aebd34414f |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:38 p.m.