Triple
T19454171
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Benny's Burgers |
E486692
|
entity |
| Predicate | hasGenreTrope |
P120127
|
FINISHED |
| Object | small-town diner as key plot location |
—
|
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: small-town diner as key plot location | Statement: [Benny's Burgers, hasGenreTrope, small-town diner as key plot location]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGenreTrope Context triple: [Benny's Burgers, hasGenreTrope, small-town diner as key plot location]
-
A.
hasGenreFeature
chosen
Indicates that something possesses a characteristic, element, or trait associated with a particular genre.
-
B.
hasGenreInRoles
Indicates that an entity participates in roles associated with a particular genre or set of genres.
-
C.
hasGenreOfClaim
Indicates that a claim is categorized or classified under a particular genre or type of claim.
-
D.
hasUseGenre
Indicates that something (such as a work, product, or item) is associated with or categorized under a particular genre for its use or purpose.
-
E.
hasGenreAsSetting
Indicates that a work’s setting is characterized by, or takes place within, 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_69d8e8d86d608190bd199a98d0297f27 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e633c117ac8190a38c01c3191beaea |
completed | April 20, 2026, 2:10 p.m. |
| PD | Predicate disambiguation | batch_69e4fd7499a4819082bec0be8afba35c |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 1:38 p.m.