Triple
T10293285
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sara "Sway" Wayland |
E241415
|
entity |
| Predicate | genreOfFictionalCharacter |
P68359
|
FINISHED |
| Object | crime |
—
|
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: crime | Statement: [Sara "Sway" Wayland, genreOfFictionalCharacter, crime]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genreOfFictionalCharacter Context triple: [Sara "Sway" Wayland, genreOfFictionalCharacter, crime]
-
A.
genreOfCharacter
chosen
Indicates that a character belongs to or is associated with a particular genre (such as fantasy, horror, or comedy).
-
B.
fictionalGenre
Indicates that a work of fiction belongs to or is categorized under a particular narrative genre or style.
-
C.
genreRole
Indicates a relationship where an entity holds a specific functional or categorical role within a particular genre.
-
D.
fictionalCharacter
Indicates that one entity is a fictional character that appears within the narrative world of another entity (such as a work, series, or franchise).
-
E.
literaryGenreOfWork
Indicates that a work belongs to or is classified under a particular literary 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_69d381aaafc08190af475ef58dc16aba |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d2d46fb08190b7694290692e47dc |
completed | April 7, 2026, 9:48 a.m. |
| PD | Predicate disambiguation | batch_69d4d1f35e548190be3b4d92d65d2d20 |
completed | April 7, 2026, 9:44 a.m. |
Created at: April 6, 2026, 11:42 a.m.