Triple

T32498615
Position Surface form Disambiguated ID Type / Status
Subject PKCS #7 E830591 entity
Predicate successor P78 FINISHED
Object Cryptographic Message Syntax
Cryptographic Message Syntax is a widely used standard for securing digital messages through encryption, digital signatures, and certificates, commonly employed in email and other data protection protocols.
E830590 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: Cryptographic Message Syntax | Statement: [PKCS #7, successor, Cryptographic Message Syntax]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Cryptographic Message Syntax
Triple: [PKCS #7, successor, Cryptographic Message Syntax]
Generated description
Cryptographic Message Syntax is a widely used standard for securing digital messages through encryption, digital signatures, and certificates, commonly employed in email and other data protection protocols.

Provenance (5 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_69f349219cb8819087e120f509629c1b completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6c441b8c88190ade9e43a3cd77f3f completed May 3, 2026, 3:42 a.m.
NED1 Entity disambiguation (via context triple) batch_6a349e9faa60819098aca83794256981 completed June 19, 2026, 1:42 a.m.
NEDg Description generation batch_6a349f6592688190b12151bd9c3fe88a completed June 19, 2026, 1:46 a.m.
NED2 Entity disambiguation (via description) batch_6a34a1136c6881909ba05be90baba354 completed June 19, 2026, 1:53 a.m.
Created at: May 1, 2026, 12:59 a.m.