Triple

T13717449
Position Surface form Disambiguated ID Type / Status
Subject Swishahouse E328938 entity
Predicate associatedWith P37 FINISHED
Object Magno
Magno is an American rapper from Houston, Texas, known for his work in the Southern hip hop scene and collaborations with the Swishahouse collective.
 E1058278 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: Magno | Statement: [Swishahouse, associatedWith, Magno]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Magno
Context triple: [Swishahouse, associatedWith, Magno]
  • A. Magnus
    Magnus is the honorific cognomen meaning "the Great," famously borne by the Roman general and statesman Pompey.
  • B. Magnus
    Magnus is a character in the 1933 historical drama film "Queen Christina," which stars Greta Garbo as the Swedish monarch.
  • C. Magnus
    Magnus is a surname of likely Scandinavian or Latin origin, shared by various notable individuals including astronaut Sandra Magnus.
  • D. Magnus
    Magnus is the real name of Magneto, the powerful mutant supervillain and sometimes antihero from Marvel's X-Men universe.
  • E. Magnus
    Magnus is a character in the stage musical adaptation of Anne Rice’s "The Vampire Chronicles," serving as a pivotal figure in the origin of Lestat’s vampirism.
  • 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: Magno
Triple: [Swishahouse, associatedWith, Magno]
Generated description
Magno is an American rapper from Houston, Texas, known for his work in the Southern hip hop scene and collaborations with the Swishahouse collective.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Magno
Target entity description: Magno is an American rapper from Houston, Texas, known for his work in the Southern hip hop scene and collaborations with the Swishahouse collective.
  • A. Magnus
    Magnus is the honorific cognomen meaning "the Great," famously borne by the Roman general and statesman Pompey.
  • B. Magnus
    Magnus is a character in the 1933 historical drama film "Queen Christina," which stars Greta Garbo as the Swedish monarch.
  • C. Magnus
    Magnus is a surname of likely Scandinavian or Latin origin, shared by various notable individuals including astronaut Sandra Magnus.
  • D. Magnus
    Magnus is the real name of Magneto, the powerful mutant supervillain and sometimes antihero from Marvel's X-Men universe.
  • E. Magnus
    Magnus is a character in the stage musical adaptation of Anne Rice’s "The Vampire Chronicles," serving as a pivotal figure in the origin of Lestat’s vampirism.
  • 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_69d80770b9bc81909f70c8c317d53cff completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dd4398f0448190810c840a82228706 completed April 13, 2026, 7:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69f79d5878948190a2aaab2ba31bd1ed completed May 3, 2026, 7:09 p.m.
NEDg Description generation batch_69f79e9e6ff88190b031fb1403cacabc completed May 3, 2026, 7:14 p.m.
NED2 Entity disambiguation (via description) batch_69f7a2d6e7ec81908a4cbc324e793c24 completed May 3, 2026, 7:32 p.m.
Created at: April 9, 2026, 9:54 p.m.