Triple

T33379486
Position Surface form Disambiguated ID Type / Status
Subject Danny Bonaduce E854731 entity
Predicate birthName P65 FINISHED
Object Dante Daniel Bonaduce
Dante Daniel Bonaduce is an American actor, radio and television personality, and former child star best known for his role on the 1970s sitcom "The Partridge Family."
E2049658 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: Dante Daniel Bonaduce | Statement: [Danny Bonaduce, birthName, Dante Daniel Bonaduce]
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: Dante Daniel Bonaduce
Triple: [Danny Bonaduce, birthName, Dante Daniel Bonaduce]
Generated description
Dante Daniel Bonaduce is an American actor, radio and television personality, and former child star best known for his role on the 1970s sitcom "The Partridge Family."

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_69f3496ca10c8190908640d18fa00832 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6e00056e48190bc18e65edef5dd98 completed May 3, 2026, 5:41 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3576e649ac81908832d2faf4cdba6f completed June 19, 2026, 5:05 p.m.
NEDg Description generation batch_6a3577f5f4348190bd0c4d9a262127a8 completed June 19, 2026, 5:10 p.m.
NED2 Entity disambiguation (via description) batch_6a3578ce5b1c8190a2e0a5361a39dd80 completed June 19, 2026, 5:13 p.m.
Created at: May 1, 2026, 1:35 a.m.