Triple
T16019991
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sweet Caroline |
E388573
|
entity |
| Predicate | hasNotableLyricFeature |
P104602
|
FINISHED |
| Object | call-and-response audience participation |
—
|
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: call-and-response audience participation | Statement: [Sweet Caroline, hasNotableLyricFeature, call-and-response audience participation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableLyricFeature Context triple: [Sweet Caroline, hasNotableLyricFeature, call-and-response audience participation]
-
A.
hasLyricsFeature
chosen
Indicates that something possesses a particular characteristic or attribute related to its lyrics.
-
B.
hasLyric
Indicates that one entity (typically a musical work or track) contains or is associated with the lyrics provided by another entity.
-
C.
notableSongCharacteristic
Indicates that a song is distinguished by a particular notable feature or quality, such as style, structure, or performance trait.
-
D.
hasNoLyrics
Indicates that the referenced musical work or audio track does not contain any sung or spoken lyrics.
-
E.
hasLyricsIn
Indicates that the lyrics of a work are written or available in a specified language.
- 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_69d86dabcb7c8190b6a39d6831d2fa1b |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1858a00888190b8505071575dc56f |
completed | April 17, 2026, 12:57 a.m. |
| PD | Predicate disambiguation | batch_69e1826a4f7c8190aba6d4f1075141b0 |
completed | April 17, 2026, 12:44 a.m. |
Created at: April 10, 2026, 4:55 a.m.