Triple
T35622963
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stan Freberg Presents the United States of America |
E1029367
|
entity |
| Predicate | adaptationAs |
P183463
|
FINISHED |
| Object | radio series |
—
|
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: radio series | Statement: [Stan Freberg Presents the United States of America, adaptationAs, radio series]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: adaptationAs Context triple: [Stan Freberg Presents the United States of America, adaptationAs, radio series]
-
A.
adaptationIn
Indicates that something appears, is represented, or takes place within a particular adaptation of an original work.
-
B.
adaptation
Indicates a relationship where one entity changes or is modified to better suit, function within, or correspond to another entity or context.
-
C.
adaptationInvolvedIn
Indicates that an adaptation process plays a causal or functional role in bringing about or participating in a specified biological or system-level outcome.
-
D.
adaptationType
Indicates the specific kind or category of adaptation that relates one entity to another or to a particular context.
-
E.
adaptationBy
Indicates a relationship where one entity has been modified, transformed, or reworked by another entity into a new form or version.
- 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_69f76e0709408190bbe322bf1707ef6b |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f79f7340e4819092a1a47f7028e63f |
completed | May 3, 2026, 7:18 p.m. |
| PD | Predicate disambiguation | batch_69f79e4bdbcc8190be7a0d2cf8a77b64 |
completed | May 3, 2026, 7:13 p.m. |
| PDg | Predicate description generation | batch_69f79ec14ce08190b22cee0b40d33743 |
completed | May 3, 2026, 7:15 p.m. |
Created at: May 3, 2026, 4:05 p.m.