Triple

T9837111
Position Surface form Disambiguated ID Type / Status
Subject Spawn of the North E239129 entity
Predicate hasCastMember P2308 FINISHED
Object Lynne Overman E357410 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: Lynne Overman | Statement: [Spawn of the North, hasCastMember, Lynne Overman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lynne Overman
Context triple: [Spawn of the North, hasCastMember, Lynne Overman]
  • A. Lynne Overman chosen
    Lynne Overman was an American character actor of the 1930s and 1940s, known for his supporting roles in Hollywood films and his distinctive, wisecracking screen persona.
  • B. Lynne Burgess
    Lynne Burgess was the wife of English novelist and composer Anthony Burgess, known primarily in relation to his life and work.
  • C. Lynne Haldeman
    Lynne Haldeman is a member of the Musk family and the sister of model and dietitian Maye Musk, making her an aunt of entrepreneur Elon Musk.
  • D. Michelle Mylett
    Michelle Mylett is a Canadian actress best known for playing Katy on the comedy series "Letterkenny."
  • E. Lynn Varley
    Lynn Varley is an American comic book colorist best known for her influential, atmospheric coloring work on Frank Miller’s graphic novels, including "The Dark Knight Returns" and "300."
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca84e314108190978324a4bdb959f8 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb33b07688190b78a70cf535c3efc completed April 2, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69d20d4079048190976eb198f8ef62f0 completed April 5, 2026, 7:20 a.m.
Created at: March 30, 2026, 8:33 p.m.