Triple

T33277203
Position Surface form Disambiguated ID Type / Status
Subject Kanal E851937 entity
Predicate filmFestivalEntry P63360 FINISHED
Object 1957 Cannes Film Festival
The 1957 Cannes Film Festival was an edition of the prestigious international film festival held in Cannes, France, showcasing notable films from around the world during the postwar era.
E2044542 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: 1957 Cannes Film Festival | Statement: [Kanal, filmFestivalEntry, 1957 Cannes Film Festival]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: 1957 Cannes Film Festival
Triple: [Kanal, filmFestivalEntry, 1957 Cannes Film Festival]
Generated description
The 1957 Cannes Film Festival was an edition of the prestigious international film festival held in Cannes, France, showcasing notable films from around the world during the postwar era.

Provenance (5 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_69f349653da08190819876015a298fdb completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6de4404b481909c33fffd9ee867c5 completed May 3, 2026, 5:33 a.m.
NED1 Entity disambiguation (via context triple) batch_6a35392207dc8190b89e5d1a97f29a00 completed June 19, 2026, 12:42 p.m.
NEDg Description generation batch_6a3539d886b88190b8c6484e86239d22 completed June 19, 2026, 12:45 p.m.
NED2 Entity disambiguation (via description) batch_6a353a48a0e08190bbd5d55a8bd390ae completed June 19, 2026, 12:47 p.m.
Created at: May 1, 2026, 1:32 a.m.