Triple
T26758294
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | All Quiet on the Western Front (1930 film) |
E674725
|
entity |
| Predicate | awardReceivedByDirector |
P172102
|
FINISHED |
| Object | Lewis Milestone |
—
|
NE NERFINISHED |
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: Lewis Milestone | Statement: [All Quiet on the Western Front (1930 film), awardReceivedByDirector, Lewis Milestone]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: awardReceivedByDirector Context triple: [All Quiet on the Western Front (1930 film), awardReceivedByDirector, Lewis Milestone]
-
A.
awardCount_AcademyAwardForBestDirector
Indicates the number of Academy Awards for Best Director that have been received.
-
B.
bestDirectorWinner
Indicates that the subject is the winner of a "Best Director" award for the object (such as a specific film, event, or year).
-
C.
awardReceivedByCastMember
Indicates that a specific award was received by a member of a production’s cast.
-
D.
numberOfAcademyAwardsForBestDirector
Indicates the total count of Academy Awards received by a director for the Best Director category.
-
E.
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.
- 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_69eecda6e9dc81908452fab3ba17ed9b |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f6a9603b208190b3533ea2b441514c |
completed | May 3, 2026, 1:48 a.m. |
| PD | Predicate disambiguation | batch_69f6a751d5e48190a77dcecbe7ef9f0b |
completed | May 3, 2026, 1:39 a.m. |
| PDg | Predicate description generation | batch_69f6a8de0b948190ae333e9cd99cbf6c |
completed | May 3, 2026, 1:46 a.m. |
Created at: April 27, 2026, 3:56 a.m.