Triple
T4625926
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charlemagne Productions |
E101095
|
entity |
| Predicate | associatedGenreTheme |
P38924
|
FINISHED |
| Object | historical concept albums |
—
|
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: historical concept albums | Statement: [Charlemagne Productions, associatedGenreTheme, historical concept albums]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedGenreTheme Context triple: [Charlemagne Productions, associatedGenreTheme, historical concept albums]
-
A.
genreAssociatedWith
chosen
Indicates a relationship where a work, item, or entity is linked to or categorized under a particular genre.
-
B.
commonGenre
Indicates that two entities share at least one genre in common.
-
C.
majorThemeAssociation
Indicates that one entity is associated with another as a primary or central theme.
-
D.
genreOfAssociatedPerson
Indicates that a particular genre is associated with a given person, such as an artist, author, or performer.
-
E.
genreWithin
Indicates that one genre is a subgenre or more specific category contained within another, broader genre.
- 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_69bd43d0497c8190ac23c65c5804846a |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5a08ef488190af46418229309b0f |
completed | March 20, 2026, 2:30 p.m. |
| PD | Predicate disambiguation | batch_69bd5231db7c8190b38d4fdbad8bf842 |
completed | March 20, 2026, 1:57 p.m. |
Created at: March 20, 2026, 1:13 p.m.