Triple

T26302921
Position Surface form Disambiguated ID Type / Status
Subject Kingston coal ash spill of 2008 E661604 entity
Predicate estimatedCleanupCost P4259 FINISHED
Object over 1 billion U.S. dollars 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: over 1 billion U.S. dollars | Statement: [Kingston coal ash spill of 2008, estimatedCleanupCost, over 1 billion U.S. dollars]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: estimatedCleanupCost
Context triple: [Kingston coal ash spill of 2008, estimatedCleanupCost, over 1 billion U.S. dollars]
  • A. estimatedCost chosen
    Indicates the predicted or calculated monetary amount expected to be required for something, such as a project, item, or action.
  • B. economicCost
    Indicates the financial burden, expense, or resource expenditure associated with an action, event, or relationship between entities.
  • C. finalCost
    Indicates the total amount to be paid for something after all calculations, such as taxes, discounts, or fees, have been applied.
  • D. computationalCost
    Indicates the amount of computing resources (such as time, memory, or processing power) required to perform a given operation or process.
  • E. estimatedCostComment
    Indicates a textual note or explanation associated with an estimated cost, such as rationale, assumptions, or additional details about that estimate.
  • 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_69ee812cd48c81908054068f545f0526 completed April 26, 2026, 9:18 p.m.
NER Named-entity recognition batch_69f612607c388190ab61d1ac7d18e08d completed May 2, 2026, 3:04 p.m.
PD Predicate disambiguation batch_69f611a9272881909093360472be832c completed May 2, 2026, 3 p.m.
Created at: April 26, 2026, 10:17 p.m.