Triple
T36144407
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Academy Award for Best Foreign Language Film for "Pelle the Conqueror" |
E1045404
|
entity |
| Predicate | awardRecipientType |
P2730
|
FINISHED |
| Object | feature 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: feature film | Statement: [Academy Award for Best Foreign Language Film for "Pelle the Conqueror", awardRecipientType, feature film]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: awardRecipientType Context triple: [Academy Award for Best Foreign Language Film for "Pelle the Conqueror", awardRecipientType, feature film]
-
A.
recipientOfAward
Indicates that an entity has received or been granted a particular award.
-
B.
awardType
Indicates the specific category or kind of award associated with an entity or event.
-
C.
typicalLaureateType
chosen
Indicates the usual or most common type or category of laureate associated with something.
-
D.
coRecipientOfAward
Indicates that two or more entities jointly received the same award.
-
E.
awardForPerformerType
Indicates that an award is designated for or associated with a specific type or category of performer.
- 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_69f76e37ace88190a906b107d388f5d1 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fdb45537288190b6791078d4a6899f |
completed | May 8, 2026, 10 a.m. |
| PD | Predicate disambiguation | batch_69fdb39ad96481908376d7def9fafc13 |
completed | May 8, 2026, 9:57 a.m. |
Created at: May 3, 2026, 4:08 p.m.