Triple
T23763003
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | One in a Million (Ne-Yo song) |
E587301
|
entity |
| Predicate | featuresSettingInMusicVideo |
P130636
|
FINISHED |
| Object | urban street |
—
|
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: urban street | Statement: [One in a Million (Ne-Yo song), featuresSettingInMusicVideo, urban street]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresSettingInMusicVideo Context triple: [One in a Million (Ne-Yo song), featuresSettingInMusicVideo, urban street]
-
A.
musicVideoFeatures
Indicates that a music video includes or prominently showcases a particular person, group, or element.
-
B.
musicVideoTone
Indicates the prevailing emotional or stylistic mood conveyed by a music video.
-
C.
usesMusicVideo
Indicates that one entity incorporates or features another entity as a music video.
-
D.
featuresMusicVideoNudity
Indicates that the music video contains depictions of nudity.
-
E.
hasMusicVideoCharacteristic
chosen
Indicates that a music video possesses a specific attribute, feature, or quality.
- 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.