Triple
T37851442
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Johanna |
E944064
|
entity |
| Predicate | festivalScreeningType |
P177920
|
FINISHED |
| Object | international film festival circuit |
—
|
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: international film festival circuit | Statement: [Johanna, festivalScreeningType, international film festival circuit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: festivalScreeningType Context triple: [Johanna, festivalScreeningType, international film festival circuit]
-
A.
filmFestivalScreening
Indicates that a film is being shown or presented as part of the official program of a film festival.
-
B.
filmFestivalCategory
Indicates the specific category or section of a film festival in which a film is entered, screened, or competes.
-
C.
festivalSelectionType
chosen
Indicates the type or category of selection an entry has within a festival (e.g., official selection, out-of-competition, special screening).
-
D.
cinemaType
Indicates the specific category or kind of cinema associated with an entity (e.g., multiplex, art house, drive-in).
-
E.
theaterType
Indicates the specific kind or category of theater associated with an entity (e.g., cinema, opera house, drama theater).
- 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_69f76eed4d9c81908b1b71ba9e3b61fe |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbbae559a8819086ef839973f8d9b2 |
completed | May 6, 2026, 10:04 p.m. |
| PD | Predicate disambiguation | batch_69fbb1440fa08190abf25ba684f75b6e |
completed | May 6, 2026, 9:23 p.m. |
Created at: May 3, 2026, 4:19 p.m.