Triple
T33548833
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ram Mohammad Thomas |
E859278
|
entity |
| Predicate | workGenreDetail |
P146635
|
FINISHED |
| Object | picaresque novel |
—
|
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: picaresque novel | Statement: [Ram Mohammad Thomas, workGenreDetail, picaresque novel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workGenreDetail Context triple: [Ram Mohammad Thomas, workGenreDetail, picaresque novel]
-
A.
hasGenreOfWorkItAppearsIn
chosen
Indicates that an entity is associated with the genre of the work in which it appears.
-
B.
genreWithin
Indicates that one genre is a subgenre or more specific category contained within another, broader genre.
-
C.
genreOfAssociatedPerson
Indicates that a particular genre is associated with a given person, such as an artist, author, or performer.
-
D.
visualGenre
Indicates the visual or stylistic category to which something belongs, such as its artistic or cinematic genre.
-
E.
genreOfRecordedWork
Indicates that a recorded work (such as a song, album, or audio piece) belongs to a particular artistic or musical 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_69f3497a5be08190a39b12736899e034 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6f70c17d88190aa74afc2dd2a0467 |
completed | May 3, 2026, 7:19 a.m. |
| PD | Predicate disambiguation | batch_69f6f6632dfc8190af85e258c8519207 |
completed | May 3, 2026, 7:16 a.m. |
Created at: May 1, 2026, 1:39 a.m.