Triple

T7934682
Position Surface form Disambiguated ID Type / Status
Subject CAST5 E184258 entity
Predicate usedIn P98 FINISHED
Object GnuPG E61959 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: GnuPG | Statement: [CAST5, usedIn, GnuPG]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: GnuPG
Context triple: [CAST5, usedIn, GnuPG]
  • A. GNU Privacy Guard chosen
    GNU Privacy Guard is a free, open-source implementation of the OpenPGP standard used for encrypting and signing data and communications.
  • B. PGP
    PGP (Pretty Good Privacy) is an encryption program that provides cryptographic privacy and authentication for data communication, most notably for securing emails and files.
  • C. Gpg4win
    Gpg4win is a Windows software suite for email and file encryption that provides an easy-to-use implementation of OpenPGP and S/MIME.
  • D. gpgsm
    gpgsm is the GNU Privacy Guard component that handles S/MIME public key cryptography, including X.509 certificate management and related operations.
  • E. gpg-agent
    gpg-agent is a background daemon for GNU Privacy Guard that securely manages private keys and handles cryptographic operations such as signing and decryption.
  • 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_69ca8290c21c8190906a5ca6fe2b03c4 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3aeb132c8190bea4906aaf51b869 completed March 31, 2026, 3:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69cb5c0791e48190af18299c22f6a804 completed March 31, 2026, 5:30 a.m.
Created at: March 30, 2026, 5:08 p.m.