Triple
T13451880
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nabi |
E320625
|
entity |
| Predicate | mentionedInGenre |
P33225
|
FINISHED |
| Object | Tafsir literature |
—
|
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: Tafsir literature | Statement: [Nabi, mentionedInGenre, Tafsir literature]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mentionedInGenre Context triple: [Nabi, mentionedInGenre, Tafsir literature]
-
A.
coveredInGenre
chosen
Indicates that a work or item is associated with, categorized under, or treated within a particular genre.
-
B.
mentionedInFilm
Indicates that an entity is referenced or talked about within the content of a film.
-
C.
featuredInFilmGenre
Indicates that an entity (such as a film, character, or work) appears in or is associated with a specific film genre.
-
D.
influencedByGenre
Indicates that something’s characteristics, style, or development are shaped or affected by a particular genre.
-
E.
hasGenreInRoles
Indicates that an entity participates in roles associated with a particular genre or set of genres.
- 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_69d80761e6cc8190a90c844589998ecc |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaefae85481909e6a59797cbb25e7 |
completed | April 12, 2026, 2:40 p.m. |
| PD | Predicate disambiguation | batch_69d9a03ce03481908c61094f0cc0c158 |
completed | April 11, 2026, 1:13 a.m. |
Created at: April 9, 2026, 9:41 p.m.