Triple

T37744198
Position Surface form Disambiguated ID Type / Status
Subject Battle of Salaspils E940801 entity
Predicate casualtiesSwedishEstimate P39830 FINISHED
Object several thousand killed or wounded 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: several thousand killed or wounded | Statement: [Battle of Salaspils, casualtiesSwedishEstimate, several thousand killed or wounded]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: casualtiesSwedishEstimate
Context triple: [Battle of Salaspils, casualtiesSwedishEstimate, several thousand killed or wounded]
  • A. SwedishCasualties chosen
    Indicates the number or extent of casualties suffered by Swedish forces or individuals in a given event or context.
  • B. casualtiesEstimate
    Indicates an estimated number of people killed, injured, or otherwise harmed as a result of an event or incident.
  • C. militaryCasualtiesEstimate
    Indicates an estimated number of people killed, wounded, or missing as a result of military conflict or operations.
  • D. nativeCasualties
    Indicates that native or indigenous people suffered deaths or injuries as a result of a particular event, action, or conflict.
  • E. casualtiesCountry
    Indicates that the specified country is the one in which the recorded casualties (deaths or injuries) occurred or to which those casualties belong.
  • 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_69f76ee0e32c8190b40a3b4cf590337c completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fbaef0cec881908c2742d77d145901 completed May 6, 2026, 9:13 p.m.
PD Predicate disambiguation batch_69fbadf632ec8190b14991c971258307 completed May 6, 2026, 9:09 p.m.
Created at: May 3, 2026, 4:19 p.m.