Triple

T26207134
Position Surface form Disambiguated ID Type / Status
Subject Kill to Get Crimson E655383 entity
Predicate hasContributor P4244 FINISHED
Object John McCusker
John McCusker is a Scottish folk musician and multi-instrumentalist, best known as a fiddler and producer who has worked extensively with artists like Mark Knopfler and on various folk and rock projects.
E1778804 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: John McCusker | Statement: [Kill to Get Crimson, hasContributor, John McCusker]
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: John McCusker
Triple: [Kill to Get Crimson, hasContributor, John McCusker]
Generated description
John McCusker is a Scottish folk musician and multi-instrumentalist, best known as a fiddler and producer who has worked extensively with artists like Mark Knopfler and on various folk and rock projects.

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_69ee5b49adb4819086545280d4ef6337 completed April 26, 2026, 6:36 p.m.
NER Named-entity recognition batch_69f60cdfd0dc8190bdf337a2333c5135 completed May 2, 2026, 2:40 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12c580e3f8819089567eaa800600a6 completed May 24, 2026, 9:31 a.m.
NEDg Description generation batch_6a12c69ac394819082dae768061147bd completed May 24, 2026, 9:36 a.m.
NED2 Entity disambiguation (via description) batch_6a12c7295270819092a8b8ef0e3488a8 completed May 24, 2026, 9:38 a.m.
Created at: April 26, 2026, 8:51 p.m.