Triple
T15628247
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frankie |
E375739
|
entity |
| Predicate | associatedWithGenreTheme |
P114508
|
FINISHED |
| Object | witchcraft |
—
|
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: witchcraft | Statement: [Frankie, associatedWithGenreTheme, witchcraft]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithGenreTheme Context triple: [Frankie, associatedWithGenreTheme, witchcraft]
-
A.
associatedWithGenreElement
chosen
Indicates that something has a connection or linkage to a specific genre-related element (such as a motif, convention, or stylistic feature).
-
B.
associatedWithGenreScene
Indicates that an entity is connected or related to a particular genre scene, such as a specific stylistic or cultural subcommunity within a broader genre.
-
C.
associatedWithGenreDevelopment
Indicates a relationship where something has contributed to, influenced, or been involved in the development or evolution of a particular genre.
-
D.
associatedWithAuthorTheme
Indicates a relationship where an author is linked to, or characterized by, a particular theme in their work or thought.
-
E.
genreAssociatedWith
Indicates a relationship where a work, item, or entity is linked to or categorized under 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_69d85cd035a48190b73d5579ab73969a |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04eb4301881908c7157227fdf79b6 |
completed | April 16, 2026, 2:51 a.m. |
| PD | Predicate disambiguation | batch_69deda868d4481908f4bce1c64d2902a |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:14 a.m.