Triple

T37257129
Position Surface form Disambiguated ID Type / Status
Subject John Redford E924160 entity
Predicate notableWork P4 FINISHED
Object In nomine (keyboard piece)
"In nomine" is a Renaissance English keyboard composition by John Redford, exemplifying the popular In nomine genre derived from a chant in John Taverner’s mass.
E2218800 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: In nomine (keyboard piece) | Statement: [John Redford, notableWork, In nomine (keyboard piece)]
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: In nomine (keyboard piece)
Triple: [John Redford, notableWork, In nomine (keyboard piece)]
Generated description
"In nomine" is a Renaissance English keyboard composition by John Redford, exemplifying the popular In nomine genre derived from a chant in John Taverner’s mass.

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_69f76eabd6c481909d414a80a1345c98 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fb372ca958819085de43635807ffba completed May 6, 2026, 12:42 p.m.
NED1 Entity disambiguation (via context triple) batch_6a4043d5e52881908b0389df16e02fd4 completed June 27, 2026, 9:42 p.m.
NEDg Description generation batch_6a404461ff1c8190ae3ed2dbedc8dc48 completed June 27, 2026, 9:45 p.m.
NED2 Entity disambiguation (via description) batch_6a40457ebde88190b43dc9291ec1b2de completed June 27, 2026, 9:49 p.m.
Created at: May 3, 2026, 4:15 p.m.