Triple

T6922370
Position Surface form Disambiguated ID Type / Status
Subject Zarma language E160218 entity
Predicate alternativeName P39 FINISHED
Object Zerma language
Zerma language is a Songhay language spoken primarily in Niger and neighboring countries, serving as a major lingua franca in the region.
 E628571 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: Zerma language | Statement: [Zarma language, alternativeName, Zerma language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Zerma language
Context triple: [Zarma language, alternativeName, Zerma language]
  • A. Kumzari language
    The Kumzari language is an endangered Southwestern Iranian language spoken primarily by the Kumzari people in the Musandam Peninsula of Oman.
  • B. Ghomara language
    The Ghomara language is a lesser-known Berber language spoken by the Ghomara people in northern Morocco.
  • C. Zabana language
    The Zabana language is an Oceanic language spoken primarily on Santa Isabel Island in the Solomon Islands.
  • D. Zay language
    Zay language is a South Ethiopic Semitic language spoken by the Zay people on islands and shores of Lake Zway in Ethiopia.
  • E. Bagirmi language
    The Bagirmi language is a Central Sudanic language spoken primarily in Chad by the Bagirmi people, known for its role as a regional lingua franca and its rich oral tradition.
  • 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: Zerma language
Triple: [Zarma language, alternativeName, Zerma language]
Generated description
Zerma language is a Songhay language spoken primarily in Niger and neighboring countries, serving as a major lingua franca in the region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Zerma language
Target entity description: Zerma language is a Songhay language spoken primarily in Niger and neighboring countries, serving as a major lingua franca in the region.
  • A. Kumzari language
    The Kumzari language is an endangered Southwestern Iranian language spoken primarily by the Kumzari people in the Musandam Peninsula of Oman.
  • B. Ghomara language
    The Ghomara language is a lesser-known Berber language spoken by the Ghomara people in northern Morocco.
  • C. Zabana language
    The Zabana language is an Oceanic language spoken primarily on Santa Isabel Island in the Solomon Islands.
  • D. Zay language
    Zay language is a South Ethiopic Semitic language spoken by the Zay people on islands and shores of Lake Zway in Ethiopia.
  • E. Bagirmi language
    The Bagirmi language is a Central Sudanic language spoken primarily in Chad by the Bagirmi people, known for its role as a regional lingua franca and its rich oral tradition.
  • 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_69c6884d350081908d8a970e4d40ad78 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6d9fd159c819092a69d1a24e22dd5 completed March 27, 2026, 7:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69c75137dd848190b35ff72725f886ba completed March 28, 2026, 3:55 a.m.
NEDg Description generation batch_69c751ebf4f48190bb206dd9c1d8bc7b completed March 28, 2026, 3:58 a.m.
NED2 Entity disambiguation (via description) batch_69c75264e65081908859551feaf1006c completed March 28, 2026, 4 a.m.
Created at: March 27, 2026, 2:26 p.m.