Triple
T7963269
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RunDown Funk U Up |
E184930
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Do You Like the Koko? |
E597041
|
NE 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: Do You Like the Koko? | Statement: [RunDown Funk U Up, hasPart, Do You Like the Koko?]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Do You Like the Koko? Context triple: [RunDown Funk U Up, hasPart, Do You Like the Koko?]
-
A.
American Koko
American Koko is a satirical mystery web series that follows a quirky private investigator navigating race, identity, and social awkwardness in modern America.
-
B.
Kokovoko
Kokovoko is the fictional, remote South Pacific island homeland of Queequeg in Herman Melville’s novel "Moby-Dick."
-
C.
What'chu Like
"What'chu Like" is a 1999 hip hop single by Da Brat featuring Tyrese, best known for its smooth, R&B-infused sound and commercial success on the Billboard charts.
-
D.
Doowutchyalike
chosen
"Doowutchyalike" is a 1989 funk-infused hip hop party track by Digital Underground known for its playful lyrics, heavy Parliament-Funkadelic influence, and early showcase of the group's eccentric style.
-
E.
COCO
COCO is a large-scale, richly annotated image dataset widely used in computer vision research for tasks like object detection, segmentation, and captioning.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca8293a2388190aace944d7ed9c0c0 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3b9f577481908589d10fdc486abb |
completed | March 31, 2026, 3:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cbe093f00881909317eb4dd4fa1393 |
completed | March 31, 2026, 2:56 p.m. |
Created at: March 30, 2026, 5:12 p.m.