Triple

T9949728
Position Surface form Disambiguated ID Type / Status
Subject Great Flood of 1879 E195297 entity
Predicate impactOnEngineering P15961 FINISHED
Object improvements in dike construction along the Tisza 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: improvements in dike construction along the Tisza | Statement: [Great Flood of 1879, impactOnEngineering, improvements in dike construction along the Tisza]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: impactOnEngineering
Context triple: [Great Flood of 1879, impactOnEngineering, improvements in dike construction along the Tisza]
  • A. hasEngineeringSignificance chosen
    Indicates that something holds notable importance, impact, or relevance within an engineering context or for engineering activities.
  • B. engineeringEmphasis
    Indicates that something places a primary focus or specialization on engineering principles, methods, or activities.
  • C. impactOnIndustry
    Indicates the effect or influence that one entity, event, or action has on the state, performance, or development of an industry.
  • D. impactBuilding
    Indicates that one entity physically collides with or strikes a building, causing an impact event.
  • E. infrastructureImpact
    Indicates the effect that an action, event, or entity has on the condition, performance, or availability of infrastructure systems.
  • 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_69ca82e96a108190932bd1fc4acd73a0 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdb65a4e6c8190968192a24aad1b7d completed April 2, 2026, 12:20 a.m.
PD Predicate disambiguation batch_69cd1d97c44081908730071269f07712 completed April 1, 2026, 1:28 p.m.
Created at: March 30, 2026, 8:45 p.m.