Triple
T26733908
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dig In |
E674051
|
entity |
| Predicate | hasPositiveLyricsTheme |
P60903
|
FINISHED |
| Object | motivation |
—
|
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: motivation | Statement: [Dig In, hasPositiveLyricsTheme, motivation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPositiveLyricsTheme Context triple: [Dig In, hasPositiveLyricsTheme, motivation]
-
A.
hasLyricsTheme
Indicates that the lyrics of a work primarily concern or revolve around a specified theme or subject.
-
B.
hasLyricalTheme
Indicates that one entity (typically a creative work) features or is characterized by a particular lyrical subject, topic, or theme.
-
C.
isInspirationalSong
Indicates that a song motivates, uplifts, or positively influences listeners through its message, emotion, or impact.
-
D.
hasRomanticLyrics
Indicates that the subject contains or features lyrics expressing romantic feelings, themes, or relationships.
-
E.
hasLyricsTone
chosen
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_69eecda57ab481909424e98f2835e7d8 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f7516d5b4081908588a6feb541f355 |
completed | May 3, 2026, 1:45 p.m. |
| PD | Predicate disambiguation | batch_69f74d40ebb081909daf60623e38f41d |
completed | May 3, 2026, 1:27 p.m. |
Created at: April 27, 2026, 3:46 a.m.