Triple
T1115407
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Academy Award for Best Actress |
E11087
|
entity |
| Predicate | awardedForYear |
P15480
|
FINISHED |
| Object | films released in the previous 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: films released in the previous year | Statement: [Academy Award for Best Actress, awardedForYear, films released in the previous year]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: awardedForYear Context triple: [Academy Award for Best Actress, awardedForYear, films released in the previous year]
-
A.
awardReceivedYear
Indicates the specific year in which an entity received a particular award.
-
B.
awardedForYearOfRelease
chosen
Indicates that an award is given in recognition of a work based on the year in which that work was released.
-
C.
awardFor
Indicates that something is given or granted as recognition or a prize for a particular achievement, work, or contribution.
-
D.
awardConferred
Indicates that an award or honor has been formally granted by one entity to another.
-
E.
awardNominationYear
Indicates the year in which an entity received a nomination for 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_69a493252a648190ac48f8742474a5e8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4bbd92a8c8190a16e55f3f739010f |
completed | March 1, 2026, 10:21 p.m. |
| PD | Predicate disambiguation | batch_69a4bb42990c819080db96478fd4977e |
completed | March 1, 2026, 10:18 p.m. |
Created at: March 1, 2026, 7:43 p.m.