Triple
T24712923
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mama Africa |
E612077
|
entity |
| Predicate | hasFilmFestivalSection |
P44901
|
FINISHED |
| Object | Berlinale Special |
—
|
NE NERFINISHED |
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: Berlinale Special | Statement: [Mama Africa, hasFilmFestivalSection, Berlinale Special]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFilmFestivalSection Context triple: [Mama Africa, hasFilmFestivalSection, Berlinale Special]
-
A.
hasFilmFestival
Indicates that a place, organization, or context hosts, organizes, or is the venue for a film festival.
-
B.
associatedFilmFestivalSection
chosen
Indicates the specific film festival section or program in which a work is included or with which it is formally linked.
-
C.
filmFestivalAwardedAt
Indicates that a particular film festival award was given or presented at a specific film festival event or edition.
-
D.
usedInFestival
Indicates that something is employed, featured, or utilized as part of a festival or festival-related activities.
-
E.
hasFestivalSection
Indicates that something includes or is associated with a specific section or category within a festival.
- 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_69e2c4d9c24c8190a3712d74327f0c6e |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f47b865df48190bf4b6d3e9f9305e6 |
completed | May 1, 2026, 10:08 a.m. |
| PD | Predicate disambiguation | batch_69f4682c8a3c8190adbfaac99474eaaf |
completed | May 1, 2026, 8:45 a.m. |
Created at: April 18, 2026, 3:25 a.m.