Triple

T2102913
Position Surface form Disambiguated ID Type / Status
Subject Exposure E37130 entity
Predicate author P4 FINISHED
Object Wilfred Owen E5953 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: Wilfred Owen | Statement: [Exposure, author, Wilfred Owen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wilfred Owen
Context triple: [Exposure, author, Wilfred Owen]
  • A. Wilfred Owen chosen
    Wilfred Owen was a renowned English poet best known for his poignant and powerful World War I poetry that exposed the brutal realities of trench warfare.
  • B. Siegfried Sassoon
    Siegfried Sassoon was a British poet, soldier, and memoirist best known for his fierce anti-war verse and his influential role in shaping World War I poetry.
  • C. Rupert Brooke
    Rupert Brooke was an English poet best known for his idealistic war sonnets written during the early stages of World War I.
  • D. Edward Marsh
    Edward Marsh was a British civil servant, patron of the arts, and influential literary figure best known for championing and editing early 20th-century Georgian poets.
  • E. Claude Binyon
    Claude Binyon was an American screenwriter and director known for his work on numerous Hollywood comedies and dramas from the 1930s through the 1950s.
  • 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_69a8861828948190924aa30c08806b3a completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69abbabe1e9081908ea66c5406e2f1d9 completed March 7, 2026, 5:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae652fc57881908eaec85edfebeb15 completed March 9, 2026, 6:14 a.m.
Created at: March 4, 2026, 7:43 p.m.