Triple
T2152889
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SIFF Cinema Uptown |
E47819
|
entity |
| Predicate | alsoScreens |
P23550
|
FINISHED |
| Object | foreign-language films |
—
|
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: foreign-language films | Statement: [SIFF Cinema Uptown, alsoScreens, foreign-language films]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: alsoScreens Context triple: [SIFF Cinema Uptown, alsoScreens, foreign-language films]
-
A.
displays
chosen
Indicates that one entity visually presents or shows another entity’s content or information.
-
B.
alsoCovers
Indicates that something extends its scope or applicability to include an additional subject, area, or case beyond what was originally covered.
-
C.
alsoUsedIn
Indicates that something is additionally employed, applied, or present in another context, setting, or use case beyond the primary one.
-
D.
screenDebut
Indicates the event or relationship in which an entity appears on screen for the first time in a film, television, or other visual media production.
-
E.
showsThat
Indicates that one entity demonstrates, proves, or provides evidence for the truth or validity of another.
- F. None of above.
Provenance (3 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_69a88a1d1fd8819088b34990d69a712f |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abbe4a3b608190b3bd5d8e28534090 |
completed | March 7, 2026, 5:57 a.m. |
| PD | Predicate disambiguation | batch_69abbd9a60648190b20b116be5c7ad98 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:44 p.m.