Triple

T36674020
Position Surface form Disambiguated ID Type / Status
Subject Pula Film Festival E905494 entity
Predicate mainAward P5653 FINISHED
Object Golden Arena for Best Director
The Golden Arena for Best Director is a prestigious filmmaking award presented at Croatia’s Pula Film Festival to honor outstanding achievement in film direction.
E2195278 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: Golden Arena for Best Director | Statement: [Pula Film Festival, mainAward, Golden Arena for Best Director]
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: Golden Arena for Best Director
Triple: [Pula Film Festival, mainAward, Golden Arena for Best Director]
Generated description
The Golden Arena for Best Director is a prestigious filmmaking award presented at Croatia’s Pula Film Festival to honor outstanding achievement in film direction.

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_69f76e6f10008190aea41746aa1b186e completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f7c7a1039c81909c83c12714d86cb0 completed May 3, 2026, 10:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3a381d57d481908e982f60bfb59da3 completed June 23, 2026, 7:39 a.m.
NEDg Description generation batch_6a3a38cef65c8190a4c5dafe793fcf7c completed June 23, 2026, 7:42 a.m.
NED2 Entity disambiguation (via description) batch_6a3a3a51dabc81909cf57f44ec196576 completed June 23, 2026, 7:48 a.m.
Created at: May 3, 2026, 4:12 p.m.