Triple

T7522496
Position Surface form Disambiguated ID Type / Status
Subject Battle of Dresden E177805 entity
Predicate casualtiesAndLossesSide1Approx P661 FINISHED
Object around 10000 French and allied casualties 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: around 10000 French and allied casualties | Statement: [Battle of Dresden, casualtiesAndLossesSide1Approx, around 10000 French and allied casualties]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: casualtiesAndLossesSide1Approx
Context triple: [Battle of Dresden, casualtiesAndLossesSide1Approx, around 10000 French and allied casualties]
  • A. militaryCasualtiesEstimate
    Indicates an estimated number of people killed, wounded, or missing as a result of military conflict or operations.
  • B. casualtiesUnion
    Indicates a relationship where multiple casualty figures or reports are combined into a single aggregated total.
  • C. casualtiesEstimate chosen
    Indicates an estimated number of people killed, injured, or otherwise harmed as a result of an event or incident.
  • D. casualties_British_side
    Indicates the number or extent of casualties suffered by the British side in a conflict or incident.
  • E. casualtiesAllied
    Indicates the number or extent of losses (killed, wounded, or missing) suffered by allied forces in a conflict or incident.
  • 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_69c69f29bf3081909a146aec7755f185 completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f7c3c4c08190ad418978afcc98ec completed March 27, 2026, 9:33 p.m.
PD Predicate disambiguation batch_69c6f4d6bb808190bdd04499fd3bceb6 completed March 27, 2026, 9:21 p.m.
Created at: March 27, 2026, 3:46 p.m.