Triple
T18691114
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Professor Bertram Potts |
E457001
|
entity |
| Predicate | storyGenreContext |
P14
|
FINISHED |
| Object | romantic comedy |
—
|
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 comedy | Statement: [Professor Bertram Potts, storyGenreContext, romantic comedy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: storyGenreContext Context triple: [Professor Bertram Potts, storyGenreContext, romantic comedy]
-
A.
literaryGenreOfWork
Indicates that a work belongs to or is classified under a particular literary genre.
-
B.
gameGenreContext
Indicates the genre or type of game associated with a given game entity or gaming context.
-
C.
genre
chosen
Indicates the artistic or thematic category to which a work (such as a book, film, or song) belongs.
-
D.
genreWithin
Indicates that one genre is a subgenre or more specific category contained within another, broader genre.
-
E.
storyElement
Indicates that one entity functions as a narrative component or part within the structure of another entity’s story.
- 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_69d8d391eb488190ac2e9abf5bf255e4 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e562e3a6d08190b2409bcbf0c42444 |
completed | April 19, 2026, 11:18 p.m. |
| PD | Predicate disambiguation | batch_69e478de85088190ba5f005f1d39f587 |
completed | April 19, 2026, 6:40 a.m. |
Created at: April 10, 2026, 11:49 a.m.