Triple

T8261452
Position Surface form Disambiguated ID Type / Status
Subject Hurricane Irma E193203 entity
Predicate damageDescription P81550 FINISHED
Object one of the costliest tropical cyclones on record 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: one of the costliest tropical cyclones on record | Statement: [Hurricane Irma, damageDescription, one of the costliest tropical cyclones on record]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: damageDescription
Context triple: [Hurricane Irma, damageDescription, one of the costliest tropical cyclones on record]
  • A. damageAssociatedWith
    Indicates a relationship where one entity is linked to causing, contributing to, or being responsible for damage affecting another entity.
  • B. damageLeadsTo
    Indicates that one instance of damage causally results in or contributes to another specified outcome or condition.
  • C. damageTo
    Indicates a relationship where one entity causes harm, loss, or deterioration to another entity.
  • D. damageAdjusted
    Indicates that the amount of damage has been modified from its original value, typically to account for mitigating or amplifying factors.
  • E. sufferedDamageTo
    Indicates that one entity has experienced harm, loss, or deterioration affecting another entity or one of its parts.
  • F. None of above. chosen

Provenance (4 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_69ca82e081d48190986beaa51f498ab9 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7936b72c8190b998da033df611d1 completed March 31, 2026, 7:35 a.m.
PD Predicate disambiguation batch_69cb36b8707881909aca349230495a5a completed March 31, 2026, 2:51 a.m.
PDg Predicate description generation batch_69cb4ab5162c8190bddd696078689895 completed March 31, 2026, 4:16 a.m.
Created at: March 30, 2026, 5:49 p.m.