Triple
T10212280
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1935 Oscars |
E242357
|
entity |
| Predicate | bestWritingCategoryName |
P92741
|
FINISHED |
| Object | Best 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: Best Adaptation | Statement: [1935 Oscars, bestWritingCategoryName, Best Adaptation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bestWritingCategoryName Context triple: [1935 Oscars, bestWritingCategoryName, Best Adaptation]
-
A.
textCategory
Indicates that a piece of text belongs to or is classified under a particular category or type.
-
B.
bestWritingOriginalStoryWinner
Indicates that the subject is the winner of an award or recognition for best writing of an original story.
-
C.
writingFocus
Indicates that an entity’s primary attention or effort is directed toward writing or written expression.
-
D.
bestWritingScreenplayWinner
Indicates that the subject is the entity that won the award for best writing (screenplay) for the associated work or event.
-
E.
writingComponent
Indicates that one entity is a written part or element that contributes to the composition or structure of another entity.
- F. None of above. chosen
Provenance (4 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_69d381ae26c48190985abd0e25ee5d04 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d3aa23bce881909b5deac612ec22cb |
completed | April 6, 2026, 12:42 p.m. |
| PD | Predicate disambiguation | batch_69d39559e5ac8190b88eca75956b7e6a |
completed | April 6, 2026, 11:13 a.m. |
| PDg | Predicate description generation | batch_69d3aa208c248190a0fb186b106389f3 |
completed | April 6, 2026, 12:42 p.m. |
Created at: April 6, 2026, 11:02 a.m.