Triple

T32900591
Position Surface form Disambiguated ID Type / Status
Subject Berlinale Palast E841597 entity
Predicate hosts P186 FINISHED
Object Berlinale opening ceremony
The Berlinale opening ceremony is the formal gala event that launches the Berlin International Film Festival, featuring red-carpet arrivals, presentations, and the first major film premiere of the program.
E2027288 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: Berlinale opening ceremony | Statement: [Berlinale Palast, hosts, Berlinale opening ceremony]
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: Berlinale opening ceremony
Triple: [Berlinale Palast, hosts, Berlinale opening ceremony]
Generated description
The Berlinale opening ceremony is the formal gala event that launches the Berlin International Film Festival, featuring red-carpet arrivals, presentations, and the first major film premiere of the program.

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_69f34945ae408190b72d8118c83beb77 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6d078b280819089530504ffd1d763 completed May 3, 2026, 4:35 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34c690beec8190aa328025e13ee565 completed June 19, 2026, 4:33 a.m.
NEDg Description generation batch_6a34c8099fcc8190a33a3dcf68af6e3c completed June 19, 2026, 4:39 a.m.
NED2 Entity disambiguation (via description) batch_6a34c884ca608190ac64f8cf72d50d18 completed June 19, 2026, 4:41 a.m.
Created at: May 1, 2026, 1:19 a.m.