Triple

T18011421
Position Surface form Disambiguated ID Type / Status
Subject Treachery E430891 entity
Predicate writer P1360 FINISHED
Object Alyssa Lobit 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: Alyssa Lobit | Statement: [Treachery, writer, Alyssa Lobit]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alyssa Lobit
Context triple: [Treachery, writer, Alyssa Lobit]
  • A. Alyssa Lobit chosen
    Alyssa Lobit is an American screenwriter, producer, and actress known for her work in independent genre films.
  • B. Katie Luber
    Katie Luber is an American art museum director and curator known for leading major institutions, including the Minneapolis Institute of Art.
  • C. Caitlin Bassett
    Caitlin Bassett is a former Australian netball star renowned as one of the world’s leading goal shooters and a key figure in multiple international championship victories for the Diamonds.
  • D. Kelsey Asbille
    Kelsey Asbille is an American actress known for her roles in television series such as Yellowstone and Teen Wolf, as well as films like Wind River.
  • E. Kaitlyn Robrock
    Kaitlyn Robrock is an American voice actress best known for portraying iconic animated characters, including serving as the current voice of Minnie Mouse for Disney.
  • 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_69d8b904530081908bf341d842464856 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4b51fc108819089e6c130a89811bc completed April 19, 2026, 10:57 a.m.
Created at: April 10, 2026, 10:24 a.m.