Triple
T36922268
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Akira Kurosawa Award |
E913234
|
entity |
| Predicate | isARecognitionOf |
P186693
|
FINISHED |
| Object | artistic excellence in film |
—
|
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: artistic excellence in film | Statement: [Akira Kurosawa Award, isARecognitionOf, artistic excellence in film]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isARecognitionOf Context triple: [Akira Kurosawa Award, isARecognitionOf, artistic excellence in film]
-
A.
wasRecognizedAs
Indicates that an entity was formally identified, acknowledged, or designated as having a particular role, status, or quality.
-
B.
seeksRecognitionOf
Indicates that one entity actively pursues acknowledgment, validation, or formal recognition from another entity.
-
C.
confersRecognition
Indicates that one entity formally acknowledges, honors, or grants recognition to another entity for some quality, status, or achievement.
-
D.
wasRecognizedIn
Indicates that an entity received acknowledgment, credit, or an award within a specified context, event, or time frame.
-
E.
grantsRecognitionTo
Indicates that one entity formally acknowledges, honors, or validates another entity’s achievements, status, or contributions.
- 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_69f76e885b848190bad82c87e9525486 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f9fe1a1ca4819084c196f0041f0be2 |
completed | May 5, 2026, 2:26 p.m. |
| PD | Predicate disambiguation | batch_69f7cf79ddb08190a083405cccc14137 |
completed | May 3, 2026, 10:43 p.m. |
| PDg | Predicate description generation | batch_69f9fd66eed48190bdc26a8def328c2d |
completed | May 5, 2026, 2:23 p.m. |
Created at: May 3, 2026, 4:13 p.m.