Triple

T29415393
Position Surface form Disambiguated ID Type / Status
Subject John Raitt E746011 entity
Predicate notableWork P4 FINISHED
Object An Evening with John Raitt
An Evening with John Raitt is a live performance recording showcasing Broadway baritone John Raitt singing and reflecting on highlights from his celebrated musical theatre career.
 E1866544 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: An Evening with John Raitt | Statement: [John Raitt, notableWork, An Evening with John Raitt]
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: An Evening with John Raitt
Triple: [John Raitt, notableWork, An Evening with John Raitt]
Generated description
An Evening with John Raitt is a live performance recording showcasing Broadway baritone John Raitt singing and reflecting on highlights from his celebrated musical theatre career.

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_69f0a79f6d5c8190a350baed0157e06f completed April 28, 2026, 12:27 p.m.
NER Named-entity recognition batch_69f66a6468ec8190a43ed6cd8c797f42 completed May 2, 2026, 9:19 p.m.
NED1 Entity disambiguation (via context triple) batch_6a25d922d3e481909347765739deec5a completed June 7, 2026, 8:48 p.m.
NEDg Description generation batch_6a25dd22d2508190a97caed70b554c2b completed June 7, 2026, 9:05 p.m.
NED2 Entity disambiguation (via description) batch_6a25e14c99008190a2761feec54a279c completed June 7, 2026, 9:23 p.m.
Created at: April 28, 2026, 3 p.m.