Triple

T16567874
Position Surface form Disambiguated ID Type / Status
Subject Mandara language E402508 entity
Predicate neighboringLanguage P16383 FINISHED
Object Mafa language
The Mafa language is a Chadic language spoken by the Mafa people primarily in northern Cameroon and parts of northeastern Nigeria.
 E1221466 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: Mafa language | Statement: [Mandara language, neighboringLanguage, Mafa language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mafa language
Context triple: [Mandara language, neighboringLanguage, Mafa language]
  • A. Mambae language
    The Mambae language is an Austronesian language spoken primarily in East Timor, notable for its role in local identity and traditional culture.
  • B. Mawase language
    The Mawase language is a Papuan language spoken in the Eastern Trans-Fly region of southern New Guinea.
  • C. Bafia language
    The Bafia language is a Bantu language spoken primarily by the Bafia people in central Cameroon.
  • D. Marau language
    The Marau language is an Oceanic language spoken in the Solomon Islands, belonging to the Southeast Solomonic branch of the Austronesian language family.
  • E. Madi language
    The Madi language is a Central Sudanic language spoken primarily by the Madi people in parts of South Sudan and northern Uganda.
  • 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: Mafa language
Triple: [Mandara language, neighboringLanguage, Mafa language]
Generated description
The Mafa language is a Chadic language spoken by the Mafa people primarily in northern Cameroon and parts of northeastern Nigeria.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mafa language
Target entity description: The Mafa language is a Chadic language spoken by the Mafa people primarily in northern Cameroon and parts of northeastern Nigeria.
  • A. Mambae language
    The Mambae language is an Austronesian language spoken primarily in East Timor, notable for its role in local identity and traditional culture.
  • B. Mawase language
    The Mawase language is a Papuan language spoken in the Eastern Trans-Fly region of southern New Guinea.
  • C. Bafia language
    The Bafia language is a Bantu language spoken primarily by the Bafia people in central Cameroon.
  • D. Marau language
    The Marau language is an Oceanic language spoken in the Solomon Islands, belonging to the Southeast Solomonic branch of the Austronesian language family.
  • E. Madi language
    The Madi language is a Central Sudanic language spoken primarily by the Madi people in parts of South Sudan and northern Uganda.
  • 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_69d8838648088190acf97ef11fc3f61b completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e35772f6608190a125c7d3c199c3e2 completed April 18, 2026, 10:05 a.m.
NED1 Entity disambiguation (via context triple) batch_6a006ee3dcbc819087ea66b262585232 completed May 10, 2026, 11:41 a.m.
NEDg Description generation batch_6a006ff5bdb88190be90d7446e24b61f completed May 10, 2026, 11:45 a.m.
NED2 Entity disambiguation (via description) batch_6a007088fd988190b3dfef081769d03e completed May 10, 2026, 11:48 a.m.
Created at: April 10, 2026, 5:16 a.m.