Triple

T23567198
Position Surface form Disambiguated ID Type / Status
Subject Dusty... Definitely E579402 entity
Predicate arranger P4873 FINISHED
Object Wally Stott
Wally Stott, later known as Angela Morley, was a renowned British composer and arranger celebrated for her work in light orchestral music, film and television scores, and collaborations with popular singers.
E1600508 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: Wally Stott | Statement: [Dusty... Definitely, arranger, Wally Stott]
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: Wally Stott
Triple: [Dusty... Definitely, arranger, Wally Stott]
Generated description
Wally Stott, later known as Angela Morley, was a renowned British composer and arranger celebrated for her work in light orchestral music, film and television scores, and collaborations with popular singers.

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_69e245fe24588190888f3aec8407d8e3 completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f1af6d3dcc8190bb127632e101a053 completed April 29, 2026, 7:12 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f5386e880819083ff2e63d8d30657 completed May 21, 2026, 6:48 p.m.
NEDg Description generation batch_6a0f579b03d881909aa6ea3d79a030fa completed May 21, 2026, 7:06 p.m.
NED2 Entity disambiguation (via description) batch_6a0f581d81f88190aa2299118feb3faa completed May 21, 2026, 7:08 p.m.
Created at: April 17, 2026, 6:35 p.m.