Triple
T15931334
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orizzonti Award for Best Film |
E386329
|
entity |
| Predicate | hasSectionTheme |
P61999
|
FINISHED |
| Object | horizons of new cinema |
—
|
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: horizons of new cinema | Statement: [Orizzonti Award for Best Film, hasSectionTheme, horizons of new cinema]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSectionTheme Context triple: [Orizzonti Award for Best Film, hasSectionTheme, horizons of new cinema]
-
A.
hasSectionColor
Indicates that an entity possesses a section (or part) characterized by a specific color.
-
B.
hasThemeType
Indicates that something is associated with or characterized by a particular thematic category or type.
-
C.
hasSectionOn
Indicates that one entity (typically a document or resource) contains a dedicated section or part that specifically addresses or discusses another entity or topic.
-
D.
hasThemingDetail
chosen
Indicates that something includes or is associated with a specific thematic element, motif, or stylistic detail.
-
E.
hasSectionWith
Indicates that an entity contains or includes a specific section that satisfies certain conditions or characteristics.
- 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_69d86da750008190987eb26be3f6c118 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e172b48b308190bc430b2308cbc75b |
completed | April 16, 2026, 11:37 p.m. |
| PD | Predicate disambiguation | batch_69e142cf5c548190a931f7b58144cd31 |
completed | April 16, 2026, 8:13 p.m. |
Created at: April 10, 2026, 4:52 a.m.