Triple

T19539691
Position Surface form Disambiguated ID Type / Status
Subject Sara Braun E488862 entity
Predicate name P16 FINISHED
Object Sara Braun NE NERFINISHED

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: Sara Braun | Statement: [Sara Braun, name, Sara Braun]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sara Braun
Context triple: [Sara Braun, name, Sara Braun]
  • A. Sara Braun chosen
    Sara Braun was a prominent late 19th- and early 20th-century businesswoman and philanthropist in Chilean Patagonia, known for her influential role in regional development and society.
  • B. Sara Haden
    Sara Haden was an American character actress best known for her supporting roles in classic Hollywood films of the 1930s and 1940s, including several entries in the Andy Hardy series.
  • C. Jen Braun
    Jen Braun is an American musician best known as a member of the early 1990s indie pop band Tiger Trap associated with the K Records scene.
  • D. Sara Hess
    Sara Hess is an American television writer and producer known for her work on acclaimed series such as House of the Dragon and Orange Is the New Black.
  • E. Sara Samuels
    Sara Samuels is the central character in the "Black Mirror" episode "Arkangel," a young girl whose life is tightly controlled and surveilled through experimental parental technology.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e8db5b6c8190984b61f91981f575 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e63871d00881909ed7371ae5577957 completed April 20, 2026, 2:30 p.m.
Created at: April 10, 2026, 1:41 p.m.