Triple
T20946495
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Samson et Dalila |
E515856
|
entity |
| Predicate | originalIntendedGenre |
P82410
|
FINISHED |
| Object | oratorio |
—
|
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: oratorio | Statement: [Samson et Dalila, originalIntendedGenre, oratorio]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalIntendedGenre Context triple: [Samson et Dalila, originalIntendedGenre, oratorio]
-
A.
primarySourceGenre
Indicates the genre or type of creative work that serves as the primary source for something (e.g., an adaptation, derivative work, or related resource).
-
B.
targetGenre
chosen
Indicates the genre that something is specifically aimed at, categorized under, or intended to belong to.
-
C.
secondaryGenre
Indicates that an entity (such as a work or item) has an additional, non-primary genre classification associated with it.
-
D.
favoriteGenre
Indicates that one entity’s preferred or most liked genre, among several possible genres, is the other entity.
-
E.
visualGenre
Indicates the visual or stylistic category to which something belongs, such as its artistic or cinematic 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_69e0b4fcd678819087a304291f14330a |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6fad97aa48190b4be692e3afce8c9 |
completed | April 21, 2026, 4:19 a.m. |
| PD | Predicate disambiguation | batch_69e5c9b1bae48190a845165fed1b005e |
completed | April 20, 2026, 6:37 a.m. |
Created at: April 16, 2026, 12:56 p.m.