Triple

T36410526
Position Surface form Disambiguated ID Type / Status
Subject Viola Tree E896863 entity
Predicate notableWork P4 FINISHED
Object The Burnt Offering
The Burnt Offering is a notable work by the artist Viola Tree, reflecting her creative output beyond her better-known career as an English actress, singer, and writer.
E2182350 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: The Burnt Offering | Statement: [Viola Tree, notableWork, The Burnt Offering]
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: The Burnt Offering
Triple: [Viola Tree, notableWork, The Burnt Offering]
Generated description
The Burnt Offering is a notable work by the artist Viola Tree, reflecting her creative output beyond her better-known career as an English actress, singer, and writer.

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_69f76e54ce408190849acc3f7758937c completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7bd2f658881909fd16c60f0af12f4 completed May 3, 2026, 9:25 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39b44adc6c8190adcc00e09c0e97d5 completed June 22, 2026, 10:16 p.m.
NEDg Description generation batch_6a39b4df5d448190a7f617a00dd640ba completed June 22, 2026, 10:19 p.m.
NED2 Entity disambiguation (via description) batch_6a39b89a393c81908a46f2f5ff13ab1a completed June 22, 2026, 10:35 p.m.
Created at: May 3, 2026, 4:10 p.m.