Triple
T15674253
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Herman Blume |
E377395
|
entity |
| Predicate | hasGenreOfWorkHeAppearsIn |
P41614
|
FINISHED |
| Object | comedy-drama film |
—
|
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: comedy-drama film | Statement: [Herman Blume, hasGenreOfWorkHeAppearsIn, comedy-drama film]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGenreOfWorkHeAppearsIn Context triple: [Herman Blume, hasGenreOfWorkHeAppearsIn, comedy-drama film]
-
A.
belongsToWorkGenre
Indicates that a creative work is classified under or associated with a particular genre.
-
B.
hasGenreInRoles
Indicates that an entity participates in roles associated with a particular genre or set of genres.
-
C.
genreOfWorkActedIn
chosen
Indicates that an entity is the genre category of a work in which another entity performed or acted.
-
D.
seriesGenreOfNotableWork
Indicates that a particular genre characterizes the notable work associated with a series.
-
E.
workedOnGenre
Indicates that an entity (such as a person or organization) has done work related to a particular 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_69d85cd2e28481909d4e975bee20872f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04f2c996c8190a9ebe0e92608feaa |
completed | April 16, 2026, 2:53 a.m. |
| PD | Predicate disambiguation | batch_69deda8b36a4819081cb5708fe77ef51 |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:16 a.m.