Triple
T2305406
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pollyanna (1920 film) |
E51826
|
entity |
| Predicate | hasAdaptationType |
P2375
|
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: [Pollyanna (1920 film), hasAdaptationType, literary adaptation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAdaptationType Context triple: [Pollyanna (1920 film), hasAdaptationType, literary adaptation]
-
A.
hasMediaAdaptation
Indicates that a work has been adapted into another medium, such as film, television, or other forms of media.
-
B.
canBeAdaptedBy
Indicates that one entity is capable of being modified, adjusted, or tailored for use by another entity.
-
C.
adaptedTo
Indicates that one entity has been modified, adjusted, or evolved to function effectively within the conditions, requirements, or characteristics defined by another entity.
-
D.
adaptationType
chosen
Indicates the specific kind or category of adaptation that relates one entity to another or to a particular context.
-
E.
transmissionTypeSupported
Indicates that a particular type of transmission is compatible with or can be used by a given system, device, or component.
- 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_69a88b0bb30c81908ded03b006d29387 |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abce1f4f0c8190a714e4dcb8449f7e |
completed | March 7, 2026, 7:05 a.m. |
| PD | Predicate disambiguation | batch_69abc58ce2a081908ce2f0cadd92e9f8 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:49 p.m.