Triple

T21374328
Position Surface form Disambiguated ID Type / Status
Subject Swan Records E527156 entity
Predicate foundedBy P104 FINISHED
Object Tony Mammarella
Tony Mammarella was an American television producer and music industry executive best known for his work on "American Bandstand" and for helping shape early rock and roll through ventures like Swan Records.
E1754699 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: Tony Mammarella | Statement: [Swan Records, foundedBy, Tony Mammarella]
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: Tony Mammarella
Triple: [Swan Records, foundedBy, Tony Mammarella]
Generated description
Tony Mammarella was an American television producer and music industry executive best known for his work on "American Bandstand" and for helping shape early rock and roll through ventures like Swan Records.

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_69e0b51e80808190ba5cb05667af02a9 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e8b0b3666c8190a83bb32eeba24105 completed April 22, 2026, 11:27 a.m.
NED1 Entity disambiguation (via context triple) batch_6a123a7c8c988190b02b617218d24837 completed May 23, 2026, 11:38 p.m.
NEDg Description generation batch_6a123ce435c4819089f35fef6d750b2f completed May 23, 2026, 11:48 p.m.
NED2 Entity disambiguation (via description) batch_6a123d4c0b248190a0a514789d0b4607 completed May 23, 2026, 11:50 p.m.
Created at: April 16, 2026, 5:10 p.m.