Triple

T12770400
Position Surface form Disambiguated ID Type / Status
Subject Vimy Ridge E305232 entity
Predicate battleCasualtiesCanadianKilled P94437 FINISHED
Object over 3,500 Canadian soldiers killed LITERAL 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: over 3,500 Canadian soldiers killed | Statement: [Vimy Ridge, battleCasualtiesCanadianKilled, over 3,500 Canadian soldiers killed]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: battleCasualtiesCanadianKilled
Context triple: [Vimy Ridge, battleCasualtiesCanadianKilled, over 3,500 Canadian soldiers killed]
  • A. CanadianCasualtiesApprox chosen
    Indicates an approximate number or estimate of Canadian casualties resulting from a particular event or situation.
  • B. NATOcasualtiesMilitaryKilled
    Indicates that members of NATO military forces were killed as casualties.
  • C. nativeCasualties
    Indicates that native or indigenous people suffered deaths or injuries as a result of a particular event, action, or conflict.
  • D. UScasualties
    Indicates the number or occurrence of casualties suffered by the United States in a given conflict, event, or situation.
  • E. englishCasualtiesKilledAndWounded
    Indicates the number of English individuals who were either killed or wounded as a result of a particular event or conflict.
  • F. None of above.

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_69d7bdf2b43c819098ae5aa68e61ea58 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96df4b36c81909bcc913dd5e535f8 completed April 10, 2026, 9:39 p.m.
PD Predicate disambiguation batch_69d96409739881909174ba005a986cb5 completed April 10, 2026, 8:56 p.m.
Created at: April 9, 2026, 5:28 p.m.