Triple

T22027374
Position Surface form Disambiguated ID Type / Status
Subject RFC 3489 E544001 entity
Predicate author P4 FINISHED
Object Jonathan Rosenberg
Jonathan Rosenberg is a computer scientist and Internet engineer best known for his influential work on real-time communications protocols such as SIP and related IETF standards.
E1712756 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: Jonathan Rosenberg | Statement: [RFC 3489, author, Jonathan Rosenberg]
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: Jonathan Rosenberg
Triple: [RFC 3489, author, Jonathan Rosenberg]
Generated description
Jonathan Rosenberg is a computer scientist and Internet engineer best known for his influential work on real-time communications protocols such as SIP and related IETF standards.

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_69e11e2e8ea4819084210fe06d3a1b8d completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f127ccc2ec8190a94d69530d00c06c completed April 28, 2026, 9:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a118532500c819090062bcd7f3eeb8f completed May 23, 2026, 10:45 a.m.
NEDg Description generation batch_6a1185c3841081909a717baf5f3a38fb completed May 23, 2026, 10:47 a.m.
NED2 Entity disambiguation (via description) batch_6a11864330048190a6b55f72fb7c89c1 completed May 23, 2026, 10:49 a.m.
Created at: April 16, 2026, 8:24 p.m.