Triple
T32902597
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | the Dutchman |
E841650
|
entity |
| Predicate | genreOfWorkFeaturingCharacter |
P55464
|
FINISHED |
| Object | Romantic opera |
—
|
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: Romantic opera | Statement: [the Dutchman, genreOfWorkFeaturingCharacter, Romantic opera]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genreOfWorkFeaturingCharacter Context triple: [the Dutchman, genreOfWorkFeaturingCharacter, Romantic opera]
-
A.
genreOfWorkCharacterIsIn
chosen
Indicates the specific genre of the creative work in which a given character appears.
-
B.
publisherOfWorksFeaturingCharacter
Indicates that one entity is the publisher responsible for releasing works in which a given character appears.
-
C.
characterInBookBy
Indicates that a character appears in a book that was written by a specified author.
-
D.
directorCharacterOf
Indicates that a director is responsible for directing a particular character in a work (e.g., film, TV show, or play).
-
E.
fictionalCharacterPortrayedFromWorkBy
Indicates that a fictional character is depicted or portrayed in a work that was created by a specific author or creator.
- 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_69f34946a5208190bbd79f0fec4323bd |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f7308a096081909d66a56f3c926806 |
completed | May 3, 2026, 11:24 a.m. |
| PD | Predicate disambiguation | batch_69f72a00c5f081908b6539d15baf4e12 |
completed | May 3, 2026, 10:57 a.m. |
Created at: May 1, 2026, 1:19 a.m.