Triple

T33801743
Position Surface form Disambiguated ID Type / Status
Subject Les Vandyke E866237 entity
Predicate alsoKnownAs P39 FINISHED
Object Johnny Worth
Johnny Worth, better known by his songwriting pseudonym Les Vandyke, was a British pop songwriter and singer noted for penning numerous UK hits in the 1960s.
E2068111 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: Johnny Worth | Statement: [Les Vandyke, alsoKnownAs, Johnny Worth]
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: Johnny Worth
Triple: [Les Vandyke, alsoKnownAs, Johnny Worth]
Generated description
Johnny Worth, better known by his songwriting pseudonym Les Vandyke, was a British pop songwriter and singer noted for penning numerous UK hits in the 1960s.

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_69f3499057fc81909d862b1309a3bd71 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6ff4ad30c8190b1eabaa000a6bf77 completed May 3, 2026, 7:54 a.m.
NED1 Entity disambiguation (via context triple) batch_6a366599883c8190a319dcf124bdf1b8 completed June 20, 2026, 10:04 a.m.
NEDg Description generation batch_6a36665237cc8190bc8377bb72784058 completed June 20, 2026, 10:07 a.m.
NED2 Entity disambiguation (via description) batch_6a36676a438881909d01a02d62eccfdc completed June 20, 2026, 10:11 a.m.
Created at: May 1, 2026, 1:46 a.m.