Triple

T29670847
Position Surface form Disambiguated ID Type / Status
Subject Franke and the Knockouts E750666 entity
Predicate hasMember P10 FINISHED
Object Tommy Ayers
Tommy Ayers is a musician best known as a member of the early-1980s American pop rock band Franke and the Knockouts.
E1881551 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: Tommy Ayers | Statement: [Franke and the Knockouts, hasMember, Tommy Ayers]
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: Tommy Ayers
Triple: [Franke and the Knockouts, hasMember, Tommy Ayers]
Generated description
Tommy Ayers is a musician best known as a member of the early-1980s American pop rock band Franke and the Knockouts.

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_69f0d62418a08190a401b127adf9f8a6 completed April 28, 2026, 3:45 p.m.
NER Named-entity recognition batch_69f671c79eb8819094e835d9ad691032 completed May 2, 2026, 9:51 p.m.
NED1 Entity disambiguation (via context triple) batch_6a26aa69ceb8819084ea8dfe42608572 completed June 8, 2026, 11:41 a.m.
NEDg Description generation batch_6a26b01a27148190aa0135f779819255 completed June 8, 2026, 12:05 p.m.
NED2 Entity disambiguation (via description) batch_6a26b4faf2c881909f77e6c4a8dc665b completed June 8, 2026, 12:26 p.m.
Created at: April 28, 2026, 7:04 p.m.