Triple
T25075368
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Probability Broach |
E628030
|
entity |
| Predicate | adaptationIllustrator |
P9707
|
FINISHED |
| Object | Scott Bieser |
—
|
NE NERFINISHED |
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: Scott Bieser | Statement: [The Probability Broach, adaptationIllustrator, Scott Bieser]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: adaptationIllustrator Context triple: [The Probability Broach, adaptationIllustrator, Scott Bieser]
-
A.
adaptedFromIllustrator
Indicates that one entity is an adaptation or derivative work based on the illustrative work created by another entity.
-
B.
illustrator
chosen
Indicates that one entity serves as the illustrator (creator of visual artwork or drawings) for another entity, such as a book, article, or other work.
-
C.
adaptationCreator
Indicates that one entity is the creator or originator of an adaptation (such as a derivative work or modified version) of another entity.
-
D.
adaptationIn
Indicates that something appears, is represented, or takes place within a particular adaptation of an original work.
-
E.
adaptationType
Indicates the specific kind or category of adaptation that relates one entity to another or to a particular context.
- 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_69e2ff2e73f881909992bf3eda5c25cb |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f45d188208819095eae1c605b12df0 |
completed | May 1, 2026, 7:58 a.m. |
| PD | Predicate disambiguation | batch_69f442c861188190967655c6d8012380 |
completed | May 1, 2026, 6:06 a.m. |
Created at: April 18, 2026, 6:21 a.m.