Triple
T34779198
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Unison Films |
E1002593
|
entity |
| Predicate | workOnAdaptationOf |
P102761
|
FINISHED |
| Object | classic literature |
—
|
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: classic literature | Statement: [Unison Films, workOnAdaptationOf, classic literature]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workOnAdaptationOf Context triple: [Unison Films, workOnAdaptationOf, classic literature]
-
A.
workAdaptedFor
Indicates that one work has been modified or transformed to create another work specifically suited for a different medium, context, or audience.
-
B.
workAdaptedIn
Indicates that a work has been transformed or re-created into another medium or format, such as a book adapted into a film, play, or other derivative work.
-
C.
adaptsWorkOf
chosen
Indicates that one entity modifies, transforms, or reinterprets the work created by another entity into a new form or context.
-
D.
basedOnWorkAdaptations
Indicates that one work is an adaptation derived from, or created on the basis of, another pre-existing work.
-
E.
basedOnWorkAdaptedTo
Indicates that one work is derived from and adapted based on the content, story, or elements of another pre-existing work.
- 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_69f76db30a108190bb57ca95b873e5bb |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f77ffa6b68819090257fed3802c239 |
completed | May 3, 2026, 5:03 p.m. |
| PD | Predicate disambiguation | batch_69f7795978c481909e152cd1bd02dd07 |
completed | May 3, 2026, 4:35 p.m. |
Created at: May 3, 2026, 3:59 p.m.