Triple

T35150969
Position Surface form Disambiguated ID Type / Status
Subject Karachi monsoon floods E1014987 entity
Predicate exposesVulnerabilityOf P119540 FINISHED
Object Karachi drainage infrastructure 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: Karachi drainage infrastructure | Statement: [Karachi monsoon floods, exposesVulnerabilityOf, Karachi drainage infrastructure]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: exposesVulnerabilityOf
Context triple: [Karachi monsoon floods, exposesVulnerabilityOf, Karachi drainage infrastructure]
  • A. vulnerableWhen
    Indicates that an entity is at increased risk of harm, failure, or exploitation under certain specified conditions or circumstances.
  • B. securityVulnerability
    Indicates that an entity has a weakness or flaw that could be exploited to compromise its security.
  • C. canBeExploitedFor
    Indicates that one entity is capable of being used or taken advantage of by another entity to obtain some benefit, resource, or outcome.
  • D. vulnerabilityType
    Indicates the specific kind or category of vulnerability associated with an entity or situation.
  • E. vulnerabilitySource chosen
    Indicates that one entity is the origin, cause, or contributing factor of another entity’s vulnerability or weakness.
  • 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_69f76dda7c108190a2ffd93eb6c341a7 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f78cec05a48190a2c656aee8dff956 completed May 3, 2026, 5:59 p.m.
PD Predicate disambiguation batch_69f78b9106008190930b3b3675b737d6 completed May 3, 2026, 5:53 p.m.
Created at: May 3, 2026, 4:02 p.m.