Triple
T2170644
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tower Theater |
E48414
|
entity |
| Predicate | screeningFocus |
P31
|
FINISHED |
| Object | Spanish-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: Spanish-language films | Statement: [Tower Theater, screeningFocus, Spanish-language films]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: screeningFocus Context triple: [Tower Theater, screeningFocus, Spanish-language films]
-
A.
screeningType
Indicates the specific method or category of screening applied in a screening process or evaluation.
-
B.
focusesOn
chosen
Indicates that one entity directs its attention, effort, or primary activity toward another entity or specific subject.
-
C.
focusType
Indicates the specific kind or category of focus or attention that is being applied to or associated with an entity or interaction.
-
D.
focusesBy
Indicates that one entity directs its attention, effort, or emphasis toward another entity or specific aspect of it.
-
E.
firstScreeningLocation
Indicates the location where something (such as a person, item, or case) is initially screened or evaluated for the first time.
- 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_69a88aa3faa48190995b233af6525815 |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc1559ff481908efe3f214b2570dc |
completed | March 7, 2026, 6:10 a.m. |
| PD | Predicate disambiguation | batch_69abbd9efc1c81909a65044a1ffc9038 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:45 p.m.