Triple
T824999
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ruby, Don’t Take Your Love to Town |
E17833
|
entity |
| Predicate | lyricalMotif |
P4921
|
FINISHED |
| Object | plea for fidelity |
—
|
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: plea for fidelity | Statement: [Ruby, Don’t Take Your Love to Town, lyricalMotif, plea for fidelity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lyricalMotif Context triple: [Ruby, Don’t Take Your Love to Town, lyricalMotif, plea for fidelity]
-
A.
lyricalPerspective
Indicates the narrative or point of view from which lyrics are expressed in a song or vocal piece.
-
B.
hasLyricalTheme
chosen
Indicates that one entity (typically a creative work) features or is characterized by a particular lyrical subject, topic, or theme.
-
C.
hasLyricalStyle
Indicates that one entity possesses or is characterized by a particular lyrical style in relation to another entity or context.
-
D.
notableSongCharacteristic
Indicates that a song is distinguished by a particular notable feature or quality, such as style, structure, or performance trait.
-
E.
hasLyricsTheme
Indicates that the lyrics of a work primarily concern or revolve around a specified theme or subject.
- 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_69a4937c9c188190aaa216f6b466f452 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ab7eb0a08190889463edb0e7bd59 |
completed | March 1, 2026, 9:11 p.m. |
| PD | Predicate disambiguation | batch_69a4aa781e1081909df006f730296c53 |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:38 p.m.