Triple
T345857
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Snake Pit |
E6939
|
entity |
| Predicate | filmEditingAcademyAward |
P12609
|
FINISHED |
| Object | nominated |
—
|
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: nominated | Statement: [The Snake Pit, filmEditingAcademyAward, nominated]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmEditingAcademyAward Context triple: [The Snake Pit, filmEditingAcademyAward, nominated]
-
A.
film
Indicates that an entity is a movie or cinematic work, or that a relationship involves such a movie.
-
B.
hasAcademy
Indicates that an entity possesses, operates, or is formally associated with an academy as part of its structure or offerings.
-
C.
mostAwardsFilm
Indicates that a film is the one that has received the highest number of awards within a given set or context.
-
D.
cinematographyBy
Indicates that the cinematographic work (such as the camera work or visual style of a film or video) is created or supervised by a specified person or entity.
-
E.
filmType
Indicates the specific category or genre that a film belongs to.
- 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_69a2e7951ba08190960e90823b5078f3 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2eb0240e88190bc70784772f5fa30 |
completed | Feb. 28, 2026, 1:17 p.m. |
| PD | Predicate disambiguation | batch_69a2e95451a4819090f4e4fb9b21a493 |
completed | Feb. 28, 2026, 1:10 p.m. |
| PDg | Predicate description generation | batch_69a2eae0bd7081908197bbf5c55fe647 |
completed | Feb. 28, 2026, 1:17 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.