Triple

T30904254
Position Surface form Disambiguated ID Type / Status
Subject Set Fire to Flames E787249 entity
Predicate hasMember P10 FINISHED
Object Geneviève Heistek
Geneviève Heistek is a Canadian musician best known as a member of the experimental post-rock collective Set Fire to Flames, associated with the Montreal indie music scene.
E1939335 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: Geneviève Heistek | Statement: [Set Fire to Flames, hasMember, Geneviève Heistek]
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: Geneviève Heistek
Triple: [Set Fire to Flames, hasMember, Geneviève Heistek]
Generated description
Geneviève Heistek is a Canadian musician best known as a member of the experimental post-rock collective Set Fire to Flames, associated with the Montreal indie music scene.

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_69f224bcbcb48190836df847424e4057 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f6927dd38081909f32b60565283795 completed May 3, 2026, 12:10 a.m.
NED1 Entity disambiguation (via context triple) batch_6a28e45e11a08190a99c7668b580ece9 completed June 10, 2026, 4:13 a.m.
NEDg Description generation batch_6a28e8ddc7d88190906421d0e28257d4 completed June 10, 2026, 4:32 a.m.
NED2 Entity disambiguation (via description) batch_6a28ecbbe4c081908bd77cb8b01d92ae completed June 10, 2026, 4:49 a.m.
Created at: April 29, 2026, 8:50 p.m.