Triple

T15417474
Position Surface form Disambiguated ID Type / Status
Subject Uncle Murda E369279 entity
Predicate alsoKnownAs P39 FINISHED
Object UM
UM is the alias of Uncle Murda, a Brooklyn-based American rapper known for his gritty street narratives and mixtapes.
 E1156687 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: UM | Statement: [Uncle Murda, alsoKnownAs, UM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: UM
Context triple: [Uncle Murda, alsoKnownAs, UM]
  • A. UM
    UM is the commonly used abbreviation for the University of Miami, a private research university located in Coral Gables, Florida.
  • B. UM
    UM is the regional vehicle registration code used for the district of Uckermark in the German state of Brandenburg.
  • C. UM
    UM is the stock ticker symbol for MRU, the Canadian food and pharmacy retail company Metro Inc.
  • D. UM
    UM is a public research university in Oxford, Mississippi, commonly known as "Ole Miss" and recognized for its academic programs and SEC athletics.
  • E. UM
    UM is the commonly used abbreviation for Universitas Negeri Malang, a public university in Malang, Indonesia known for its strong focus on education and teacher training.
  • 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: UM
Triple: [Uncle Murda, alsoKnownAs, UM]
Generated description
UM is the alias of Uncle Murda, a Brooklyn-based American rapper known for his gritty street narratives and mixtapes.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: UM
Target entity description: UM is the alias of Uncle Murda, a Brooklyn-based American rapper known for his gritty street narratives and mixtapes.
  • A. UM
    UM is the commonly used abbreviation for the University of Miami, a private research university located in Coral Gables, Florida.
  • B. UM
    UM is the commonly used abbreviation for Universitas Negeri Malang, a public university in Malang, Indonesia known for its strong focus on education and teacher training.
  • C. UM
    UM is the commonly used abbreviation for Finland’s Ministry for Foreign Affairs, the government body responsible for the country’s foreign policy and diplomatic relations.
  • D. UM
    UM is the commonly used abbreviation for Maastricht University, a public research university located in Maastricht, the Netherlands.
  • E. UM
    UM is the stock ticker symbol for MRU, the Canadian food and pharmacy retail company Metro Inc.
  • 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_69d85a1849f48190bf898068b2806fae completed April 10, 2026, 2:02 a.m.
NER Named-entity recognition batch_69e03ea8a8a081909749db1b29d85fcc completed April 16, 2026, 1:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff1a78f9cc819097a6ff1e0cbdbcf3 completed May 9, 2026, 11:28 a.m.
NEDg Description generation batch_69ff1bc3aa2c8190b61d21fa78682ea1 completed May 9, 2026, 11:34 a.m.
NED2 Entity disambiguation (via description) batch_69ff1cbccab48190b9e19b5a09324d8c completed May 9, 2026, 11:38 a.m.
Created at: April 10, 2026, 3:20 a.m.