Triple
T4991004
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Barchester Chronicles (BBC television serial) |
E112127
|
entity |
| Predicate | adaptationGenre |
P57201
|
FINISHED |
| Object | literary adaptation |
—
|
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 adaptation | Statement: [The Barchester Chronicles (BBC television serial), adaptationGenre, literary adaptation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: adaptationGenre Context triple: [The Barchester Chronicles (BBC television serial), adaptationGenre, literary adaptation]
-
A.
adaptationOfWorkGenre
chosen
Indicates that one work is an adaptation of another work that belongs to a specific genre.
-
B.
adaptationStar
Indicates that one work is an adaptation of another, with the subject being the adapted work and the object being the original source.
-
C.
adaptationBy
Indicates a relationship where one entity has been modified, transformed, or reworked by another entity into a new form or version.
-
D.
adaptationType
Indicates the specific kind or category of adaptation that relates one entity to another or to a particular context.
-
E.
adaptedAs
Indicates that one work, concept, or entity has been transformed or re-created into another form or medium based on the original.
- 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_69bd441be7bc8190b530362d427b97d2 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd74249a8c8190952680aee06a9286 |
completed | March 20, 2026, 4:21 p.m. |
| PD | Predicate disambiguation | batch_69bd71492dec8190af4c27a3043b35cc |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:34 p.m.