Triple

T31884504
Position Surface form Disambiguated ID Type / Status
Subject Windscale fire E813969 entity
Predicate fatalitiesEstimatedLongTerm P700 FINISHED
Object dozens to hundreds of possible cancer deaths 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: dozens to hundreds of possible cancer deaths | Statement: [Windscale fire, fatalitiesEstimatedLongTerm, dozens to hundreds of possible cancer deaths]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: fatalitiesEstimatedLongTerm
Context triple: [Windscale fire, fatalitiesEstimatedLongTerm, dozens to hundreds of possible cancer deaths]
  • A. causedFatalities
    Indicates that the referenced event or action directly resulted in one or more deaths.
  • B. indirectFatalitiesCause
    Indicates a causal relationship where an entity is responsible for deaths that occur indirectly, as a secondary or downstream consequence rather than as the immediate cause.
  • C. deathTollEstimate chosen
    Indicates an estimated number of deaths attributed to a particular event, cause, or period.
  • D. casualtiesEstimate
    Indicates an estimated number of people killed, injured, or otherwise harmed as a result of an event or incident.
  • E. numberOfPeopleLaterDyingOfInjuriesConsidered
    Indicates the number of people who subsequently died from injuries that were previously evaluated or taken into account.
  • 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_69f348ed74bc81909846aaa6a3c7318c completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6b0daa4988190b78498e7da6a30dd completed May 3, 2026, 2:20 a.m.
PD Predicate disambiguation batch_69f6aca59d4881908d14ed47962703bd completed May 3, 2026, 2:02 a.m.
Created at: April 30, 2026, 11:57 p.m.