Triple

T21494256
Position Surface form Disambiguated ID Type / Status
Subject Chinese remainder theorem E530312 entity
Predicate usedIn P98 FINISHED
Object RSA algorithm E5909 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: RSA algorithm | Statement: [Chinese remainder theorem, usedIn, RSA algorithm]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: RSA algorithm
Context triple: [Chinese remainder theorem, usedIn, RSA algorithm]
  • A. RSA chosen
    RSA is a widely used public-key cryptographic algorithm that enables secure key exchange and digital signatures in many internet security protocols.
  • B. RSA
    RSA is the three-letter World Rugby trigram used to represent the South Africa national rugby union team in international competitions and official records.
  • C. Rabin cryptosystem
    The Rabin cryptosystem is a public-key encryption scheme based on the hardness of integer factorization, notable for its provable security equivalence to factoring and its similarity to RSA.
  • D. RSA Security
    RSA Security is a pioneering American cybersecurity company best known for its contributions to public-key cryptography and secure data encryption technologies.
  • E. RSA Design
    RSA Design is a creative design division of the production company RSA Films, specializing in visual and graphic solutions for film, advertising, and branded content.
  • 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_69e0c45bd15481909fba5910765cdda2 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69e9ea567244819091863350fedae3ae completed April 23, 2026, 9:45 a.m.
NED1 Entity disambiguation (via context triple) batch_6a09e1398efc8190a6465defb1715c2b completed May 17, 2026, 3:39 p.m.
Created at: April 16, 2026, 6:23 p.m.