Triple

T849328
Position Surface form Disambiguated ID Type / Status
Subject Aldous Huxley E18347 entity
Predicate influenced P9 FINISHED
Object Margaret Atwood E3306 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: Margaret Atwood | Statement: [Aldous Huxley, influenced, Margaret Atwood]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Margaret Atwood
Context triple: [Aldous Huxley, influenced, Margaret Atwood]
  • A. Margaret Atwood chosen
    Margaret Atwood is a renowned Canadian author and poet best known for her speculative fiction works such as "The Handmaid's Tale" and "Oryx and Crake."
  • B. A. S. Byatt
    A. S. Byatt was an acclaimed English novelist, critic, and academic best known for her Booker Prize-winning novel "Possession" and her intellectually rich, intertextual fiction.
  • C. Michael Ondaatje
    Michael Ondaatje is a Sri Lankan-born Canadian novelist and poet best known for his Booker Prize–winning novel "The English Patient."
  • D. Helen Garner
    Helen Garner is an acclaimed Australian novelist, short story writer, and journalist known for her incisive explorations of everyday life, relationships, and moral complexity.
  • E. Ursula K. Le Guin
    Ursula K. Le Guin was a highly influential American author best known for her imaginative and socially insightful science fiction and fantasy works, including the Earthsea series and the Hainish Cycle.
  • 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_69a4938b04208190b82e1df6b572c548 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4ac1fac3481909cba7070ce31a9b3 completed March 1, 2026, 9:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69a792a0666c8190bfc9166d45b4e867 completed March 4, 2026, 2:02 a.m.
Created at: March 1, 2026, 7:38 p.m.