Triple

T10489362
Position Surface form Disambiguated ID Type / Status
Subject Masalit language E247373 entity
Predicate alternateName P39 FINISHED
Object Masara
Masara is an alternate name for the Masalit language, a Nilo-Saharan language spoken primarily by the Masalit people in western Sudan and eastern Chad.
 E867073 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: Masara | Statement: [Masalit language, alternateName, Masara]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Masara
Context triple: [Masalit language, alternateName, Masara]
  • A. Masar
    Masar is a British Thoroughbred racehorse best known for winning the 2018 Epsom Derby for Godolphin.
  • B. Masarra
    Masarra is a passenger station on Cairo Metro’s Line 2 serving commuters in the Cairo metropolitan area.
  • C. Masass
    Masass was a leader associated with the Northwest Indian Confederacy, a coalition of Native American tribes that resisted U.S. expansion in the late 18th and early 19th centuries.
  • D. El Maasara
    El Maasara is a district and suburban area in the southern part of Greater Cairo, Egypt, known for its residential neighborhoods and industrial zones.
  • E. Temara
    Temara is a coastal city in northwestern Morocco, situated just south of Rabat and known for its beaches and growing residential and industrial areas.
  • 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: Masara
Triple: [Masalit language, alternateName, Masara]
Generated description
Masara is an alternate name for the Masalit language, a Nilo-Saharan language spoken primarily by the Masalit people in western Sudan and eastern Chad.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Masara
Target entity description: Masara is an alternate name for the Masalit language, a Nilo-Saharan language spoken primarily by the Masalit people in western Sudan and eastern Chad.
  • A. Masar
    Masar is a British Thoroughbred racehorse best known for winning the 2018 Epsom Derby for Godolphin.
  • B. Masarra
    Masarra is a passenger station on Cairo Metro’s Line 2 serving commuters in the Cairo metropolitan area.
  • C. Masass
    Masass was a leader associated with the Northwest Indian Confederacy, a coalition of Native American tribes that resisted U.S. expansion in the late 18th and early 19th centuries.
  • D. El Maasara
    El Maasara is a district and suburban area in the southern part of Greater Cairo, Egypt, known for its residential neighborhoods and industrial zones.
  • E. Temara
    Temara is a coastal city in northwestern Morocco, situated just south of Rabat and known for its beaches and growing residential and industrial areas.
  • 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_69d381c309b88190af78aa681cf6a4c2 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d5097ca5c081908b47a08ca7885650 completed April 7, 2026, 1:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69d8dc9792308190b09d6aaed63dd418 completed April 10, 2026, 11:18 a.m.
NEDg Description generation batch_69d8e8c81bdc8190b6b6dfe00025b514 completed April 10, 2026, 12:10 p.m.
NED2 Entity disambiguation (via description) batch_69d901e1ecf88190acd24a0e20462cb9 completed April 10, 2026, 1:57 p.m.
Created at: April 6, 2026, 12:23 p.m.