Triple

T23620001
Position Surface form Disambiguated ID Type / Status
Subject Clyde Records E583288 entity
Predicate namedAfter P63 FINISHED
Object Clyde (character associated with Ray Stevens)
Clyde is a comedic, recurring character created by country singer Ray Stevens, often featured in his humorous songs and skits.
E1595830 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: Clyde (character associated with Ray Stevens) | Statement: [Clyde Records, namedAfter, Clyde (character associated with Ray Stevens)]
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: Clyde (character associated with Ray Stevens)
Triple: [Clyde Records, namedAfter, Clyde (character associated with Ray Stevens)]
Generated description
Clyde is a comedic, recurring character created by country singer Ray Stevens, often featured in his humorous songs and skits.

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_69e248fbcd9081908ba08913f9d30826 completed April 17, 2026, 2:51 p.m.
NER Named-entity recognition batch_69f1b17780a88190b6f0d6d551133454 completed April 29, 2026, 7:21 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f459865c48190b4dd42d5dd221f7c completed May 21, 2026, 5:49 p.m.
NEDg Description generation batch_6a0f4762e62c81908285cf6299f22250 completed May 21, 2026, 5:56 p.m.
NED2 Entity disambiguation (via description) batch_6a0f481aa71c8190bbbab462001d3586 completed May 21, 2026, 5:59 p.m.
Created at: April 17, 2026, 6:45 p.m.