Triple

T2002245
Position Surface form Disambiguated ID Type / Status
Subject Poly1305 E43495 entity
Predicate comparedTo P278 FINISHED
Object HMAC E37198 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: HMAC | Statement: [Poly1305, comparedTo, HMAC]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: HMAC
Context triple: [Poly1305, comparedTo, HMAC]
  • A. HMAC chosen
    HMAC (Hash-based Message Authentication Code) is a cryptographic construction that combines a secret key with a hash function to provide data integrity and authentication.
  • B. CRAM-MD5
    CRAM-MD5 is a challenge–response authentication mechanism that uses MD5 hashing to securely verify a user's identity without transmitting their password in plaintext.
  • C. Merkle–Damgård construction
    The Merkle–Damgård construction is a fundamental method for building collision-resistant cryptographic hash functions from fixed-size compression functions, used in many classic hash algorithms like MD5 and SHA-1.
  • D. Poly1305
    Poly1305 is a high-speed message authentication code (MAC) algorithm commonly used with stream ciphers like ChaCha20 to provide data integrity and authenticity.
  • E. MD5
    MD5 is a widely known but now cryptographically broken 128-bit hash function formerly used for checksums, data integrity, and security applications.
  • 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_69a88715dbbc8190b2299e29e955d997 completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb8820cec8190a945e5daeb8c9df6 completed March 7, 2026, 5:32 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae0342ef8c8190b7771076282981c3 completed March 8, 2026, 11:16 p.m.
Created at: March 4, 2026, 7:37 p.m.