Triple

T4182623
Position Surface form Disambiguated ID Type / Status
Subject Battle of Arginusae E88227 entity
Predicate casualties (Athens) P1399 FINISHED
Object significant losses in ships and sailors 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: significant losses in ships and sailors | Statement: [Battle of Arginusae, casualties (Athens), significant losses in ships and sailors]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: casualties (Athens)
Context triple: [Battle of Arginusae, casualties (Athens), significant losses in ships and sailors]
  • A. GreekCasualties
    Indicates that the relationship specifies the number or extent of casualties suffered by Greek forces or populations in a particular conflict or event.
  • B. casualties chosen
    Indicates that an event, action, or situation resulted in people being killed or injured.
  • C. casualtiesAssociatedWithEvent
    Indicates that certain casualties (deaths or injuries) are linked to, or resulted from, a specific event.
  • D. nativeCasualties
    Indicates that native or indigenous people suffered deaths or injuries as a result of a particular event, action, or conflict.
  • E. casualtiesDescription
    Indicates a textual description of the human losses (such as deaths, injuries, or missing persons) resulting from an event 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_69aed9477e8c81908bcb862d2db55b1d completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af07078cb081909f64326b12522410 completed March 9, 2026, 5:44 p.m.
PD Predicate disambiguation batch_69af019155448190b19868583272513f completed March 9, 2026, 5:21 p.m.
Created at: March 9, 2026, 3:45 p.m.