Triple
T25407923
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Academy Award for Best Actor for "My Man Godfrey" |
E636606
|
entity |
| Predicate | yearOfNomination |
P23227
|
FINISHED |
| Object | 1937 |
—
|
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: 1937 | Statement: [Academy Award for Best Actor for "My Man Godfrey", yearOfNomination, 1937]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: yearOfNomination Context triple: [Academy Award for Best Actor for "My Man Godfrey", yearOfNomination, 1937]
-
A.
awardNominationYear
chosen
Indicates the year in which an entity received a nomination for an award.
-
B.
yearOfAwardCeremony
Indicates the specific year in which an award ceremony took place.
-
C.
yearOfAchievement
Indicates the specific year in which an achievement, accomplishment, or notable milestone occurred or was obtained.
-
D.
academyAwardsSubmissionYear
Indicates the year in which a work was officially submitted for consideration to the Academy Awards.
-
E.
returnedAwardYear
Indicates the year in which an award that had previously been given was returned or relinquished.
- 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_69e75db361d881908d8701c856da6413 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f65aa07c048190a5df30d53d8f0cf5 |
completed | May 2, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69f659cc571c819097e51e531961d812 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 21, 2026, 1:52 p.m.