Triple
T3168772
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | How Green Was My Valley |
E66275
|
entity |
| Predicate | yearOfAcademyAwards |
P23227
|
FINISHED |
| Object | 14th Academy Awards |
—
|
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: 14th Academy Awards | Statement: [How Green Was My Valley, yearOfAcademyAwards, 14th Academy Awards]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: yearOfAcademyAwards Context triple: [How Green Was My Valley, yearOfAcademyAwards, 14th Academy Awards]
-
A.
awardReceivedYear
Indicates the specific year in which an entity received a particular award.
-
B.
awardedForYearOfRelease
Indicates that an award is given in recognition of a work based on the year in which that work was released.
-
C.
goldenGlobeYear
Indicates the specific year in which a Golden Globe award or nomination associated with an entity took place.
-
D.
awardNominationYear
chosen
Indicates the year in which an entity received a nomination for an award.
-
E.
academyAwardWins
Indicates that one entity has won a specified number of Academy Awards (Oscars) or that a winning relationship exists between the entity and the Academy 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_69ad8585d7988190af37365331093ccd |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada64726048190933dbdc44258703e |
completed | March 8, 2026, 4:39 p.m. |
| PD | Predicate disambiguation | batch_69ad9e0076b4819094628f1ad10b8f68 |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:06 p.m.