Triple
T788796
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | James Fenimore Cooper |
E16863
|
entity |
| Predicate | hasLiterarySetting |
P19303
|
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: [James Fenimore Cooper, hasLiterarySetting, American frontier]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLiterarySetting Context triple: [James Fenimore Cooper, hasLiterarySetting, American frontier]
-
A.
hasLiterarySignificance
Indicates that something holds notable importance, influence, or value within the realm of literature or literary studies.
-
B.
hasLiteraryForm
Indicates that one entity is expressed, structured, or realized in a particular literary form (such as a genre, style, or textual format).
-
C.
literaryFeature
Indicates a relationship where something possesses or exhibits a characteristic, device, or stylistic element used in literature.
-
D.
literarySource
Indicates that one entity serves as the written or literary origin, reference, or basis for another entity.
-
E.
literaryLanguage
Indicates that an entity is expressed, written, or communicated using a particular literary or standardized written language.
- F. None of above. chosen
Provenance (4 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_69a4936cb7448190914f5fe4b8d81607 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a782fe988190966b958673fe12bf |
completed | March 1, 2026, 8:54 p.m. |
| PD | Predicate disambiguation | batch_69a4a50ef72c819084ffe9f31dbd0262 |
completed | March 1, 2026, 8:43 p.m. |
| PDg | Predicate description generation | batch_69a4a62b497081909503c8d30c7ce1db |
completed | March 1, 2026, 8:48 p.m. |
Created at: March 1, 2026, 7:38 p.m.