Triple

T17839324
Position Surface form Disambiguated ID Type / Status
Subject Liz Muir E445478 entity
Predicate name P16 FINISHED
Object Liz Muir 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: Liz Muir | Statement: [Liz Muir, name, Liz Muir]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Liz Muir
Context triple: [Liz Muir, name, Liz Muir]
  • A. Liz Muir chosen
    Liz Muir is a notable individual associated with the surname Muir, recognized as a distinguished bearer of that name.
  • B. Moira Davidson
    Moira Davidson is a central character in Nevil Shute’s post-apocalyptic novel "On the Beach," known for her poignant transformation from a carefree socialite to a woman confronting the end of the world with courage and emotional depth.
  • C. Sheila Milne
    Sheila Milne is a notable individual recognized for sharing the Milne surname, though specific widely known public achievements or roles associated with her are not well documented.
  • D. Lorna Crozier
    Lorna Crozier is an acclaimed Canadian poet and educator known for her lyrical explorations of memory, landscape, and the human condition.
  • E. Lorna Campbell
    Lorna Campbell is a fictional British intelligence agent and key supporting character who assists the bumbling spy in the comedy film "Johnny English."
  • 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_69d8b9f1a6d881909f024bc603111cdb completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e48d2a570c81909787296bde7e795c completed April 19, 2026, 8:07 a.m.
Created at: April 10, 2026, 10:16 a.m.