Triple
T6479986
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hats Off to Larry |
E146166
|
entity |
| Predicate | primarySubjectInLyrics |
P4921
|
FINISHED |
| Object | failed romantic 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: failed romantic relationship | Statement: [Hats Off to Larry, primarySubjectInLyrics, failed romantic relationship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primarySubjectInLyrics Context triple: [Hats Off to Larry, primarySubjectInLyrics, failed romantic relationship]
-
A.
singsAbout
Indicates that one entity performs a song whose subject or theme is another entity.
-
B.
primaryTopicOf
Indicates that a given subject is the main or central topic described by another resource (such as a document, page, or record).
-
C.
primaryMotif
Indicates that one entity serves as the main recurring theme or dominant motif associated with another entity.
-
D.
lyricalMood
Indicates the prevailing emotional tone or atmosphere conveyed through lyrics or vocal expression in a piece of music.
-
E.
hasLyricalTheme
chosen
Indicates that one entity (typically a creative work) features or is characterized by a particular lyrical subject, topic, or theme.
- 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_69c008fec7408190af7b146dc63d9750 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c06a4e764c819086828bb841f588e0 |
completed | March 22, 2026, 10:16 p.m. |
| PD | Predicate disambiguation | batch_69c0673f6d48819080e10c85155c7195 |
completed | March 22, 2026, 10:03 p.m. |
Created at: March 22, 2026, 4:51 p.m.