Triple

T33557971
Position Surface form Disambiguated ID Type / Status
Subject Frank Sidebottom E859535 entity
Predicate hasAssociatedAct P2830 FINISHED
Object The Freshies
The Freshies were a late-1970s/early-1980s Manchester power pop band best known for their witty, hook-filled songs and cult UK hit “I’m in Love with a Girl on a Certain Manchester Megastore Checkout Desk.”
 E2056949 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 Freshies | Statement: [Frank Sidebottom, hasAssociatedAct, The Freshies]
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 Freshies
Triple: [Frank Sidebottom, hasAssociatedAct, The Freshies]
Generated description
The Freshies were a late-1970s/early-1980s Manchester power pop band best known for their witty, hook-filled songs and cult UK hit “I’m in Love with a Girl on a Certain Manchester Megastore Checkout Desk.”

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_69f3497b2b68819093207971b5e13dc8 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6f70fde208190b0a0c2950bc99362 completed May 3, 2026, 7:19 a.m.
NED1 Entity disambiguation (via context triple) batch_6a35afd229848190833f01203fad18d8 completed June 19, 2026, 9:08 p.m.
NEDg Description generation batch_6a35b0740af88190a4a20b7f451910bd completed June 19, 2026, 9:11 p.m.
NED2 Entity disambiguation (via description) batch_6a35b120ac408190a51a7deac3cfc57f completed June 19, 2026, 9:14 p.m.
Created at: May 1, 2026, 1:40 a.m.