Triple
T13517131
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shari Springer Berman |
E322790
|
entity |
| Predicate | workOftenFeatures |
P51454
|
FINISHED |
| Object | literary adaptations |
—
|
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: literary adaptations | Statement: [Shari Springer Berman, workOftenFeatures, literary adaptations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workOftenFeatures Context triple: [Shari Springer Berman, workOftenFeatures, literary adaptations]
-
A.
workOftenAddresses
Indicates that a work frequently deals with, discusses, or focuses on a particular topic or subject.
-
B.
workFeatured
chosen
Indicates that one work is highlighted, showcased, or given special prominence within a particular context, collection, or presentation.
-
C.
worksOver
Indicates that one entity performs work that extends beyond or exceeds a certain limit, threshold, or standard associated with another entity.
-
D.
workWith
Indicates that one entity collaborates or engages in work-related activities together with another entity.
-
E.
workOftenDepicts
Indicates that one entity’s work frequently portrays, represents, or includes the other entity as a subject or theme.
- 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_69d80766a21881909f21a1b7421d3b8a |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbafa0ed508190b2855171b1945e84 |
completed | April 12, 2026, 2:43 p.m. |
| PD | Predicate disambiguation | batch_69dbae0b63748190b5e207f84b2532ea |
completed | April 12, 2026, 2:36 p.m. |
Created at: April 9, 2026, 9:44 p.m.