Triple

T10298681
Position Surface form Disambiguated ID Type / Status
Subject Mamelodi E241565 entity
Predicate hasAlternativeName P39 FINISHED
Object Mams
Mams is a commonly used nickname for Mamelodi, a large township northeast of Pretoria in South Africa.
 E856297 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: Mams | Statement: [Mamelodi, hasAlternativeName, Mams]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mams
Context triple: [Mamelodi, hasAlternativeName, Mams]
  • A. Mam
    Mam is a Mayan language spoken primarily by the Mam people in the western highlands of Guatemala and parts of southern Mexico.
  • B. Mamiii
    "Mamiii" is a hit reggaeton song by Colombian singer Karol G, known for its empowering breakup theme and widespread commercial success across Latin music charts.
  • C. Maimies
    Maimies is an alternate historical name for the Mayaimi people, a Native American group that once inhabited the Lake Okeechobee region of present-day Florida.
  • D. Mamu
    Mamu is a notable Odia novel by Fakir Mohan Senapati that satirically portrays social and political life in colonial Odisha.
  • E. Les Muma
    Les Muma is an American businessman and philanthropist best known for his major contributions to the University of South Florida, where the business school bears his name.
  • 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: Mams
Triple: [Mamelodi, hasAlternativeName, Mams]
Generated description
Mams is a commonly used nickname for Mamelodi, a large township northeast of Pretoria in South Africa.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mams
Target entity description: Mams is a commonly used nickname for Mamelodi, a large township northeast of Pretoria in South Africa.
  • A. Mam
    Mam is a Mayan language spoken primarily by the Mam people in the western highlands of Guatemala and parts of southern Mexico.
  • B. Mamiii
    "Mamiii" is a hit reggaeton song by Colombian singer Karol G, known for its empowering breakup theme and widespread commercial success across Latin music charts.
  • C. Maimies
    Maimies is an alternate historical name for the Mayaimi people, a Native American group that once inhabited the Lake Okeechobee region of present-day Florida.
  • D. Mamu
    Mamu is a notable Odia novel by Fakir Mohan Senapati that satirically portrays social and political life in colonial Odisha.
  • E. Les Muma
    Les Muma is an American businessman and philanthropist best known for his major contributions to the University of South Florida, where the business school bears his name.
  • 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_69d381aaafc08190af475ef58dc16aba completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d2ed50908190962f0d6d049fb964 completed April 7, 2026, 9:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69d71d35d5908190bb87100c81f2948a completed April 9, 2026, 3:29 a.m.
NEDg Description generation batch_69d7318402f08190b655bdddbd97ecb9 completed April 9, 2026, 4:56 a.m.
NED2 Entity disambiguation (via description) batch_69d734473ef48190852dbe48742a4273 completed April 9, 2026, 5:08 a.m.
Created at: April 6, 2026, 11:44 a.m.