Triple
T4337793
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Over and Over |
E97504
|
entity |
| Predicate | belongsToArtistNationality |
P3285
|
FINISHED |
| Object | American (Nelly) |
—
|
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: American (Nelly) | Statement: [Over and Over, belongsToArtistNationality, American (Nelly)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: belongsToArtistNationality Context triple: [Over and Over, belongsToArtistNationality, American (Nelly)]
-
A.
primaryArtistNationality
Indicates the nationality associated with the main or primary artist involved in a work or context.
-
B.
performingArtistNationality
chosen
Indicates the nationality or country of origin of the artist who performs a given work or performance.
-
C.
featuredArtistNationality
Indicates the nationality associated with an artist who is prominently featured in a work or event.
-
D.
associatedComposerNationality
Indicates that there is a relationship between a composer and a specific nationality with which that composer is identified or associated.
-
E.
authorNationality
Indicates the relationship between an author and the country or nationality with which that author is identified.
- 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_69b3454662a481908fbcd0bbfaa3a0a4 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3516c621881909f094d040d4805e9 |
completed | March 12, 2026, 11:51 p.m. |
| PD | Predicate disambiguation | batch_69b34f4fe1c481908d6d66e15697c04b |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:14 p.m.