Triple

T14343529
Position Surface form Disambiguated ID Type / Status
Subject java.security E355658 entity
Predicate containsClass P9272 FINISHED
Object java.security.SecureRandom E355658 NE 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: java.security.SecureRandom | Statement: [java.security, containsClass, java.security.SecureRandom]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: java.security.SecureRandom
Context triple: [java.security, containsClass, java.security.SecureRandom]
  • A. java.security chosen
    java.security is a core Java package that provides the framework and APIs for implementing security features such as cryptography, access control, and secure random number generation.
  • B. MersenneTwister
    MersenneTwister is a widely used pseudorandom number generator algorithm known for its long period and high-quality statistical properties.
  • C. javax.crypto
    javax.crypto is a Java package that provides the framework and implementations for cryptographic operations such as encryption, decryption, key generation, and secure random number generation.
  • D. System.Random
    System.Random is a .NET class that provides methods for generating pseudo-random numbers for use in applications.
  • E. MRG32k3a generator
    The MRG32k3a generator is a high-quality combined multiple recursive pseudorandom number generator widely used in scientific computing and simulations for its long period and good statistical properties.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69d82790a7e08190877e2d349b2e8d8e completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de8e89ed9c8190acdb647ee618e919 completed April 14, 2026, 6:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd469d899081909103563f209dd944 completed May 8, 2026, 2:12 a.m.
Created at: April 10, 2026, 1:14 a.m.