Triple
T367744
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seattle International Film Festival |
E7999
|
entity |
| Predicate | screeningsPerEdition |
P11685
|
FINISHED |
| Object | over 400 films (approximate) |
—
|
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: over 400 films (approximate) | Statement: [Seattle International Film Festival, screeningsPerEdition, over 400 films (approximate)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: screeningsPerEdition Context triple: [Seattle International Film Festival, screeningsPerEdition, over 400 films (approximate)]
-
A.
numberOfExhibits
Indicates the total count of exhibits associated with a given entity or context.
-
B.
hasNumberOfTheatres
Indicates the quantity of theatres associated with or present in a given entity.
-
C.
servedInTheatres
Indicates that a film or performance was publicly exhibited in movie theaters or similar cinema venues.
-
D.
presentedIn
Indicates that something is shown, displayed, or formally introduced within a particular context, medium, event, or setting.
-
E.
screeningType
Indicates the specific method or category of screening applied in a screening process or evaluation.
- 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_69a2e7e880008190a6ad7e06e5d03007 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ebeab13c8190b15c2f10310ec6a8 |
completed | Feb. 28, 2026, 1:21 p.m. |
| PD | Predicate disambiguation | batch_69a2e95ede588190998fdf3a6ea90498 |
completed | Feb. 28, 2026, 1:10 p.m. |
| PDg | Predicate description generation | batch_69a2ea0b23ec8190bef9d593162388a4 |
completed | Feb. 28, 2026, 1:13 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.