Triple
T14184366
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moscow International Film Festival |
E351535
|
entity |
| Predicate | hasRedCarpetEvents |
P50870
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Moscow International Film Festival, hasRedCarpetEvents, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRedCarpetEvents Context triple: [Moscow International Film Festival, hasRedCarpetEvents, yes]
-
A.
hasRedCarpetEvent
chosen
Indicates that an entity hosts, organizes, or is associated with an event featuring a formal red-carpet arrival or ceremony.
-
B.
hasNotablePersonEvent
Indicates that there exists a significant event in which the person plays a notable or central role.
-
C.
hasFilmPremiereInDecade
Indicates that a film’s premiere or first public release occurred during a specified decade.
-
D.
hasFanPerformances
Indicates that an entity has associated performances created or carried out by fans.
-
E.
hasAwardShow
Indicates that an entity organizes, hosts, or is associated with a specific award show or ceremony.
- 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_69d8278834a08190b0f1784e58d7b99c |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61cc0a848190b660095972b1223b |
completed | April 14, 2026, 3:48 p.m. |
| PD | Predicate disambiguation | batch_69de05baed64819096590e5618a3a8ed |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 10, 2026, 1:03 a.m.