Triple

T33403078
Position Surface form Disambiguated ID Type / Status
Subject Heart Phoenix E855366 entity
Predicate spouse P13 FINISHED
Object Jeffrey Weisberg
Jeffrey Weisberg is an American documentary filmmaker and longtime partner of the late activist and social worker Heart Phoenix, mother of actors River and Joaquin Phoenix.
E2064457 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: Jeffrey Weisberg | Statement: [Heart Phoenix, spouse, Jeffrey Weisberg]
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: Jeffrey Weisberg
Triple: [Heart Phoenix, spouse, Jeffrey Weisberg]
Generated description
Jeffrey Weisberg is an American documentary filmmaker and longtime partner of the late activist and social worker Heart Phoenix, mother of actors River and Joaquin Phoenix.

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_69f3496e3f1c8190bcecfa82aa9d17ff completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6e4163d408190aea7a1dbbd24ba09 completed May 3, 2026, 5:58 a.m.
NED1 Entity disambiguation (via context triple) batch_6a365c56779c81908eb5892df750aa94 completed June 20, 2026, 9:24 a.m.
NEDg Description generation batch_6a365d415b94819095be28ce74f2e717 completed June 20, 2026, 9:28 a.m.
NED2 Entity disambiguation (via description) batch_6a365db10b648190a22055323a8393f3 completed June 20, 2026, 9:30 a.m.
Created at: May 1, 2026, 1:36 a.m.