Triple

T9350876
Position Surface form Disambiguated ID Type / Status
Subject Saint Petersburg Dam E225013 entity
Predicate designedToReduce P9925 FINISHED
Object frequency of severe floods in Saint Petersburg 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: frequency of severe floods in Saint Petersburg | Statement: [Saint Petersburg Dam, designedToReduce, frequency of severe floods in Saint Petersburg]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: designedToReduce
Context triple: [Saint Petersburg Dam, designedToReduce, frequency of severe floods in Saint Petersburg]
  • A. designedToAvoid
    Indicates that something was intentionally created or configured in a way that prevents or minimizes a particular outcome, condition, or interaction.
  • B. reduces chosen
    Indicates that one entity causes a decrease in the amount, intensity, degree, or impact of another entity.
  • C. designedToDefeat
    Indicates that one entity is intentionally created or configured with the purpose of overcoming, neutralizing, or rendering ineffective another entity.
  • D. isDesignedFor
    Indicates that one entity has been created, planned, or optimized specifically to serve the needs, purposes, or use of another entity.
  • E. designedForReusability
    Indicates that something has been intentionally created or configured so it can be used multiple times without needing to be discarded or fundamentally rebuilt.
  • 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_69ca842abfd48190949d71c3b86eeba8 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd4f9248c08190a7bb40feec2eb217 completed April 1, 2026, 5:02 p.m.
PD Predicate disambiguation batch_69cc7a68ab9481909f97cb70764697cc completed April 1, 2026, 1:52 a.m.
Created at: March 30, 2026, 7:41 p.m.