Triple
T31405645
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Academy Award for Best Actor for Pelle the Conqueror |
E801117
|
entity |
| Predicate | associatedFilmAward |
P32099
|
FINISHED |
| Object | Academy Awards |
E2155
|
NE 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: Academy Awards | Statement: [Academy Award for Best Actor for Pelle the Conqueror, associatedFilmAward, Academy Awards]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedFilmAward Context triple: [Academy Award for Best Actor for Pelle the Conqueror, associatedFilmAward, Academy Awards]
-
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.
associatedWithAwardNominatedFilm
Indicates that an entity has a relationship to a film that has been nominated for an award.
-
C.
filmWonAcademyAwardFor
Indicates that a film received an Academy Award (Oscar) in a specified category or for a particular achievement.
-
D.
mostAwardsFilm
Indicates that a film is the one that has received the highest number of awards within a given set or context.
-
E.
awardReceivedByCastMember
chosen
Indicates that a specific award was received by a member of a production’s cast.
- F. None of above.
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_69f348c0dd648190bf2fd7642f78eb06 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_6a037c876524819098545e6037d3107d |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a2ad2501a8881908aa7970d4d6c05f2 |
completed | June 11, 2026, 3:20 p.m. |
| PD | Predicate disambiguation | batch_6a0379e5174c8190a0bdde7e381b7624 |
completed | May 12, 2026, 7:05 p.m. |
Created at: April 30, 2026, 8:31 p.m.