Triple
T9720800
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ellen Grange |
E235463
|
entity |
| Predicate | setInGenreContext |
P20075
|
FINISHED |
| Object | American frontier |
—
|
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: American frontier | Statement: [Ellen Grange, setInGenreContext, American frontier]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: setInGenreContext Context triple: [Ellen Grange, setInGenreContext, American frontier]
-
A.
hasGenreAsSetting
Indicates that a work’s setting is characterized by, or takes place within, a particular genre.
-
B.
hasGenreScope
Indicates that something (such as a work, collection, or classification) is limited to, defined by, or applicable within a particular genre or set of genres.
-
C.
genreContext
chosen
Indicates the contextual genre or categorical style associated with an entity, such as the thematic or stylistic framework in which it is situated.
-
D.
hasGenreInfluenceOn
Indicates that one genre has a notable impact on shaping or influencing the characteristics, style, or development of another genre.
-
E.
belongsToWorkGenre
Indicates that a creative work is classified under or associated with 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_69ca84d0123c819096f9dc3b6abb0881 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9e419c2c8190b325d5fd692c6000 |
completed | April 1, 2026, 10:37 p.m. |
| PD | Predicate disambiguation | batch_69cd03bfeca08190924fca43aaa9c10f |
completed | April 1, 2026, 11:38 a.m. |
Created at: March 30, 2026, 8:20 p.m.