Triple
T25444027
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Academy Award for Best Actor for Midnight Cowboy |
E637580
|
entity |
| Predicate | filmWonAcademyAwardFor |
P158837
|
FINISHED |
| Object | Best Director |
—
|
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: Best Director | Statement: [Academy Award for Best Actor for Midnight Cowboy, filmWonAcademyAwardFor, Best Director]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmWonAcademyAwardFor Context triple: [Academy Award for Best Actor for Midnight Cowboy, filmWonAcademyAwardFor, Best Director]
-
A.
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.
-
B.
oscarAward
Indicates that an entity has received or been honored with an Academy Award (Oscar).
-
C.
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.
-
D.
oscarCategoryWon
Indicates that an entity has won an Academy Award in the specified Oscar category.
-
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_69e75db6c97081908178383fa632b193 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f7028a5c8190b32720973dd5f45e |
completed | May 2, 2026, 1:07 p.m. |
| PD | Predicate disambiguation | batch_69f4806d93dc8190b9dff4c63186faff |
completed | May 1, 2026, 10:29 a.m. |
| PDg | Predicate description generation | batch_69f48b9058d081908ec9af261ee092e2 |
completed | May 1, 2026, 11:16 a.m. |
Created at: April 21, 2026, 2 p.m.