Triple
T22718457
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arsamene |
E561795
|
entity |
| Predicate | hasGenreOfWorkAppearedIn |
P146635
|
FINISHED |
| Object | opera seria (with comic elements) |
—
|
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: opera seria (with comic elements) | Statement: [Arsamene, hasGenreOfWorkAppearedIn, opera seria (with comic elements)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGenreOfWorkAppearedIn Context triple: [Arsamene, hasGenreOfWorkAppearedIn, opera seria (with comic elements)]
-
A.
hasGenreOfWorkItAppearsIn
chosen
Indicates that an entity is associated with the genre of the work in which it appears.
-
B.
hasWorkInGenreOfAuthor
Indicates that a work is associated with an author whose typical or primary genre matches the genre of that work.
-
C.
workedOnGenre
Indicates that an entity (such as a person or organization) has done work related to a particular genre.
-
D.
belongsToWorkGenre
Indicates that a creative work is classified under or associated with a particular genre.
-
E.
hasWorkInGenreOfDirector
Indicates that a creator’s work belongs to the same genre as that associated with a particular director.
- 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_69e2454fc984819088213b58ee87a002 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1790fbf9c819082ba7b48801a7b39 |
completed | April 29, 2026, 3:20 a.m. |
| PD | Predicate disambiguation | batch_69ee62c24a1c819096c410906e9b173c |
completed | April 26, 2026, 7:08 p.m. |
Created at: April 17, 2026, 3:19 p.m.