Triple
T10514945
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Logorama |
E248007
|
entity |
| Predicate | title |
P38
|
FINISHED |
| Object | Logorama |
E248007
|
NE 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: Logorama | Statement: [Logorama, title, Logorama]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Logorama Context triple: [Logorama, title, Logorama]
-
A.
Logorama
chosen
Logorama is a 2009 French animated short film that satirically depicts a world made entirely of corporate logos and mascots.
-
B.
L’Avenir
L’Avenir is a historical Belgian socialist newspaper that served as a key mouthpiece for the Parti rouge.
-
C.
Dogville
Dogville is a 2003 avant-garde drama film written and directed by Lars von Trier, known for its minimalist stage-like set and allegorical exploration of human nature and cruelty.
-
D.
The Fountain
The Fountain is a 2006 science fiction romantic drama film directed by Darren Aronofsky that intertwines three narratives across time to explore themes of love, mortality, and the quest for eternal life.
-
E.
Tideland
Tideland is a dark fantasy drama film known for its surreal, disturbing portrayal of a young girl's imagination as she copes with isolation and trauma in a desolate rural setting.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d381c4aa948190942e1d803143fb0e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d509cbacb08190a446c864b97823ad |
completed | April 7, 2026, 1:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d90df141488190a2674546aa437de8 |
completed | April 10, 2026, 2:49 p.m. |
Created at: April 6, 2026, 12:27 p.m.