Triple

T37164598
Position Surface form Disambiguated ID Type / Status
Subject Blackmagic Design E920759 entity
Predicate product P490 FINISHED
Object Blackmagic Cinema Camera
The Blackmagic Cinema Camera is a professional digital film camera known for its high dynamic range, RAW recording capabilities, and affordability for independent filmmakers and video producers.
 E2215355 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: Blackmagic Cinema Camera | Statement: [Blackmagic Design, product, Blackmagic Cinema Camera]
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: Blackmagic Cinema Camera
Triple: [Blackmagic Design, product, Blackmagic Cinema Camera]
Generated description
The Blackmagic Cinema Camera is a professional digital film camera known for its high dynamic range, RAW recording capabilities, and affordability for independent filmmakers and video producers.

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_69f76ea0429081908c711b55599eac3c completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fb35c47a008190b8125bcc27bd7cbe completed May 6, 2026, 12:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a402bba279c81908800321a32b6f2c5 completed June 27, 2026, 7:59 p.m.
NEDg Description generation batch_6a402c6811ec8190826d548b0cb3e067 completed June 27, 2026, 8:02 p.m.
NED2 Entity disambiguation (via description) batch_6a402e1aa0f48190aab13b1e22d78014 completed June 27, 2026, 8:10 p.m.
Created at: May 3, 2026, 4:15 p.m.