Triple

T4357301
Position Surface form Disambiguated ID Type / Status
Subject Twisted Brown Trucker E98180 entity
Predicate hasMember P10 FINISHED
Object Paradime
Paradime is an American rapper and songwriter known for his work in the Detroit hip-hop scene and collaborations with artists like Kid Rock.
 E432784 NE FINISHED

How this triple was built (4 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: Paradime | Statement: [Twisted Brown Trucker, hasMember, Paradime]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Paradime
Context triple: [Twisted Brown Trucker, hasMember, Paradime]
  • A. Plegridy
    Plegridy is a pegylated interferon beta-1a medication used to treat relapsing forms of multiple sclerosis.
  • B. Prysm
    Prysm is a widely used Ethereum consensus client implementation written in Go that helps manage validators and secure the network under proof-of-stake.
  • C. Fremulon
    Fremulon is a television production company founded by Michael Schur, best known for producing acclaimed comedy series such as Brooklyn Nine-Nine.
  • D. Panacea
    Panacea is the Greek goddess of universal remedy and healing, associated with cures for all diseases.
  • E. Heed
    Heed is the fiercely loyal yet conflicted protagonist of Toni Morrison’s novel "Love," whose lifelong bond and rivalry with her friend Christine drive much of the story’s emotional and thematic tension.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Paradime
Triple: [Twisted Brown Trucker, hasMember, Paradime]
Generated description
Paradime is an American rapper and songwriter known for his work in the Detroit hip-hop scene and collaborations with artists like Kid Rock.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Paradime
Target entity description: Paradime is an American rapper and songwriter known for his work in the Detroit hip-hop scene and collaborations with artists like Kid Rock.
  • A. Plegridy
    Plegridy is a pegylated interferon beta-1a medication used to treat relapsing forms of multiple sclerosis.
  • B. Prysm
    Prysm is a widely used Ethereum consensus client implementation written in Go that helps manage validators and secure the network under proof-of-stake.
  • C. Fremulon
    Fremulon is a television production company founded by Michael Schur, best known for producing acclaimed comedy series such as Brooklyn Nine-Nine.
  • D. Panacea
    Panacea is the Greek goddess of universal remedy and healing, associated with cures for all diseases.
  • E. Heed
    Heed is the fiercely loyal yet conflicted protagonist of Toni Morrison’s novel "Love," whose lifelong bond and rivalry with her friend Christine drive much of the story’s emotional and thematic tension.
  • F. None of above. chosen

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_69b3454965f881908c41190bb22f0e4b completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b351c68a588190ba14a298afacb1dc completed March 12, 2026, 11:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5dbb9b9988190adf8a84de3582ab6 completed March 14, 2026, 10:05 p.m.
NEDg Description generation batch_69b5dc578b08819095cbf6ba8470d3e0 completed March 14, 2026, 10:08 p.m.
NED2 Entity disambiguation (via description) batch_69b5dd1b03508190a47bb6fb93f22ad8 completed March 14, 2026, 10:11 p.m.
Created at: March 12, 2026, 11:16 p.m.