Triple

T29414658
Position Surface form Disambiguated ID Type / Status
Subject RFC 1700 E745992 entity
Predicate author P4 FINISHED
Object Joyce K. Reynolds
Joyce K. Reynolds was an influential Internet pioneer and longtime RFC editor who played a key role in the development and documentation of core Internet protocols.
E1912781 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: Joyce K. Reynolds | Statement: [RFC 1700, author, Joyce K. Reynolds]
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: Joyce K. Reynolds
Triple: [RFC 1700, author, Joyce K. Reynolds]
Generated description
Joyce K. Reynolds was an influential Internet pioneer and longtime RFC editor who played a key role in the development and documentation of core Internet 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_69f0a79f6d5c8190a350baed0157e06f completed April 28, 2026, 12:27 p.m.
NER Named-entity recognition batch_69f66a6468ec8190a43ed6cd8c797f42 completed May 2, 2026, 9:19 p.m.
NED1 Entity disambiguation (via context triple) batch_6a278919be948190bee0a47d244a020e completed June 9, 2026, 3:31 a.m.
NEDg Description generation batch_6a278b94f650819096c9736b86c1d796 completed June 9, 2026, 3:42 a.m.
NED2 Entity disambiguation (via description) batch_6a278bf5b3e08190bdaedc14e6cf7c7d completed June 9, 2026, 3:43 a.m.
Created at: April 28, 2026, 3 p.m.