Triple

T1065100
Position Surface form Disambiguated ID Type / Status
Subject Hurricane Katrina E22990 entity
Predicate promptedReform P10613 FINISHED
Object U.S. disaster preparedness policies 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: U.S. disaster preparedness policies | Statement: [Hurricane Katrina, promptedReform, U.S. disaster preparedness policies]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: promptedReform
Context triple: [Hurricane Katrina, promptedReform, U.S. disaster preparedness policies]
  • A. reform
    Indicates bringing about significant changes to an existing system, practice, or entity in order to improve or correct it.
  • B. scriptAfterReform
    Indicates that one script or writing system is used after a reform or modification has been applied to another script.
  • C. hasReformEffort
    Indicates that an entity undertakes, is involved in, or is the subject of a deliberate effort to change, improve, or restructure a system, policy, or practice.
  • D. postReformDevelopment chosen
    Indicates the development or changes that occur after a reform has been implemented.
  • E. notableReform
    Indicates that an entity is recognized for having initiated, led, or been central to a significant reform or transformative change in a system, policy, or institution.
  • 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_69a493dada0481909c43649f9843ea91 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b90f91248190ace1534a51b82bdd completed March 1, 2026, 10:09 p.m.
PD Predicate disambiguation batch_69a4b7359eb881909c868a558861cc18 completed March 1, 2026, 10:01 p.m.
Created at: March 1, 2026, 7:42 p.m.