Triple

T31245524
Position Surface form Disambiguated ID Type / Status
Subject Every Good Boy Deserves Favour E796674 entity
Predicate composer P1361 FINISHED
Object Mike Pinder
Mike Pinder is an English musician and founding member of The Moody Blues, best known as the band's keyboardist and for pioneering the use of the Mellotron in rock music.
E796692 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: Mike Pinder | Statement: [Every Good Boy Deserves Favour, composer, Mike Pinder]
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: Mike Pinder
Triple: [Every Good Boy Deserves Favour, composer, Mike Pinder]
Generated description
Mike Pinder is an English musician and founding member of The Moody Blues, best known as the band's keyboardist and for pioneering the use of the Mellotron in rock music.

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_69f224dc84d0819081f1cb6f9127e6b1 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f69d51a73c8190aeadfcb6afc93cbb completed May 3, 2026, 12:56 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2b2d6281108190926f170507de3532 completed June 11, 2026, 9:49 p.m.
NEDg Description generation batch_6a2b2efe07548190bd55880ce8591ab8 completed June 11, 2026, 9:56 p.m.
NED2 Entity disambiguation (via description) batch_6a2b2f570f4081909f36e50ae39a4bbe completed June 11, 2026, 9:57 p.m.
Created at: April 29, 2026, 9:11 p.m.