Triple
T28656326
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Academy Award for Best Supporting Actress (won by Ruth Gordon) |
E725343
|
entity |
| Predicate | awardedForYearOfFilm |
P15480
|
FINISHED |
| Object | 1968 film year |
—
|
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: 1968 film year | Statement: [Academy Award for Best Supporting Actress (won by Ruth Gordon), awardedForYearOfFilm, 1968 film year]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: awardedForYearOfFilm Context triple: [Academy Award for Best Supporting Actress (won by Ruth Gordon), awardedForYearOfFilm, 1968 film year]
-
A.
awardedForYearOfRelease
chosen
Indicates that an award is given in recognition of a work based on the year in which that work was released.
-
B.
yearOfAwardCeremony
Indicates the specific year in which an award ceremony took place.
-
C.
returnedAwardYear
Indicates the year in which an award that had previously been given was returned or relinquished.
-
D.
AcademyAwardsYear
Indicates the specific year in which the referenced Academy Awards event took place.
-
E.
associatedAwardWinningFilm
Indicates that there is a relationship between an entity and a film with which it is connected, where that film has received an award.
- 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_69f01d84f5f0819087ab5e6143b14ed7 |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69f7308a096081909d66a56f3c926806 |
completed | May 3, 2026, 11:24 a.m. |
| PD | Predicate disambiguation | batch_69f72a00c5f081908b6539d15baf4e12 |
completed | May 3, 2026, 10:57 a.m. |
Created at: April 28, 2026, 4:55 a.m.