Triple
T13055583
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ngiculela – Es Una Historia – I Am Singing |
E327561
|
entity |
| Predicate | hasMultilingualLyrics |
P104602
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Ngiculela – Es Una Historia – I Am Singing, hasMultilingualLyrics, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMultilingualLyrics Context triple: [Ngiculela – Es Una Historia – I Am Singing, hasMultilingualLyrics, true]
-
A.
hasLyric
Indicates that one entity (typically a musical work or track) contains or is associated with the lyrics provided by another entity.
-
B.
hasLyricalVariant
Indicates that one item has an alternative version that differs in its lyrics while remaining related to the original.
-
C.
hasLyricsIn
Indicates that the lyrics of a work are written or available in a specified language.
-
D.
hasLyricsFeature
chosen
Indicates that something possesses a particular characteristic or attribute related to its lyrics.
-
E.
hasExplicitLyrics
Indicates that the referenced content contains explicit language or themes, such as profanity, sexual content, or strong violence.
- 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_69d8076e64308190904fb5c93517c901 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d98a9829b48190b23624b6b3df4600 |
completed | April 10, 2026, 11:41 p.m. |
| PD | Predicate disambiguation | batch_69d9803aca4c8190b1015cd159cc47a9 |
completed | April 10, 2026, 10:56 p.m. |
Created at: April 9, 2026, 8:58 p.m.