Triple
T5277918
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stanford Theatre |
E119417
|
entity |
| Predicate | hasTypeOfScreenings |
P9177
|
FINISHED |
| Object | 35mm film prints |
—
|
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: 35mm film prints | Statement: [Stanford Theatre, hasTypeOfScreenings, 35mm film prints]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfScreenings Context triple: [Stanford Theatre, hasTypeOfScreenings, 35mm film prints]
-
A.
screeningType
chosen
Indicates the specific method or category of screening applied in a screening process or evaluation.
-
B.
hasScreened
Indicates that one entity has shown, displayed, or evaluated another entity, typically in the context of presenting media or conducting a review or check.
-
C.
hasScreen
Indicates that an entity is equipped with or includes a screen or display component.
-
D.
screeningOutcome
Indicates the result or decision produced by a screening or evaluation process applied to an entity.
-
E.
hasNumberOfScreens
Indicates the quantity of screens associated with or contained in a given entity.
- 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_69bd446d05a8819092ad333a3f9c8d5c |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd8c9c72b08190947b6b955ac1bb5a |
completed | March 20, 2026, 6:06 p.m. |
| PD | Predicate disambiguation | batch_69bd844a56b48190ad743c42246e02dd |
completed | March 20, 2026, 5:30 p.m. |
Created at: March 20, 2026, 1:51 p.m.