Triple
T23763004
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | One in a Million (Ne-Yo song) |
E587301
|
entity |
| Predicate | featuresDanceSequencesInMusicVideo |
P35114
|
FINISHED |
| Object | Yes |
—
|
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: Yes | Statement: [One in a Million (Ne-Yo song), featuresDanceSequencesInMusicVideo, Yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresDanceSequencesInMusicVideo Context triple: [One in a Million (Ne-Yo song), featuresDanceSequencesInMusicVideo, Yes]
-
A.
hasDanceSequences
chosen
Indicates that the subject contains or features one or more dance sequences as part of its content or activity.
-
B.
hasDanceSceneWith
Indicates that two entities participate together in a dance scene within the same context or work.
-
C.
danceFeature
Indicates that one entity serves as a notable characteristic, element, or attribute of a dance or dancing-related activity.
-
D.
hasChoreographedDanceInVideo
Indicates that an entity has created or arranged the choreography for a dance that appears in a particular video.
-
E.
musicVideoChoreographer
Indicates that the subject served as the choreographer responsible for creating or directing the dance or movement in the specified music video.
- 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_69e2490b8ac48190a6b35f1d5500486b |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1bdb40ee881908f3916cc6d05fc72 |
completed | April 29, 2026, 8:13 a.m. |
| PD | Predicate disambiguation | batch_69f155f79e34819080f9ddb972b34deb |
completed | April 29, 2026, 12:51 a.m. |
Created at: April 17, 2026, 7:14 p.m.