Triple
T32284482
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kansas (fictional setting of the film) |
E824787
|
entity |
| Predicate | adaptationOfSettingFrom |
P43664
|
FINISHED |
| Object | Kansas in L. Frank Baum’s Oz books |
—
|
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: Kansas in L. Frank Baum’s Oz books | Statement: [Kansas (fictional setting of the film), adaptationOfSettingFrom, Kansas in L. Frank Baum’s Oz books]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: adaptationOfSettingFrom Context triple: [Kansas (fictional setting of the film), adaptationOfSettingFrom, Kansas in L. Frank Baum’s Oz books]
-
A.
adaptationType
Indicates the specific kind or category of adaptation that relates one entity to another or to a particular context.
-
B.
revisedSetting
Indicates that an existing setting or configuration has been modified or updated from its previous state.
-
C.
adaptationIn
Indicates that something appears, is represented, or takes place within a particular adaptation of an original work.
-
D.
isAdaptation
chosen
Indicates that one work is derived from, based on, or reinterprets the content of another work.
-
E.
adaptationOfMethod
Indicates that one method is derived from, modified based on, or tailored from another existing method.
- 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_69f3490f404081908450db66884f4334 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6f8164698819090c1b471f1caa4c6 |
completed | May 3, 2026, 7:24 a.m. |
| PD | Predicate disambiguation | batch_69f6f6619404819084662aef1238261c |
completed | May 3, 2026, 7:16 a.m. |
Created at: May 1, 2026, 12:43 a.m.