Triple
T1271469
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Academy Award for Best Makeup and Hairstyling |
E15718
|
entity |
| Predicate | isOscarCategory |
P28066
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Academy Award for Best Makeup and Hairstyling, isOscarCategory, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isOscarCategory Context triple: [Academy Award for Best Makeup and Hairstyling, isOscarCategory, true]
-
A.
oscarAward
Indicates that an entity has received or been honored with an Academy Award (Oscar).
-
B.
genreOfAwards
Indicates the type or category of awards associated with a given work, event, or entity.
-
C.
goldenGlobeAwardFor
Indicates that an entity has received a Golden Globe Award for a specified work, role, or achievement.
-
D.
goldenGlobeNomination
Indicates that an entity received a nomination for a Golden Globe award.
-
E.
bestPictureWinner
Indicates that the subject is the film that won the Best Picture award in a given context or year.
- F. None of above. chosen
Provenance (4 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_69a4935a94308190bb92555b79032824 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4c06ae7b88190a1e0b5232d84a7b1 |
completed | March 1, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69a4bede52a081909665d60acbe41d31 |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4bfa205ec81909d8170b398345615 |
completed | March 1, 2026, 10:37 p.m. |
Created at: March 1, 2026, 7:50 p.m.