Triple

T11093562
Position Surface form Disambiguated ID Type / Status
Subject Sara languages E262315 entity
Predicate hasMember P10 FINISHED
Object Ndam language
Ndam language is a Central Sudanic language spoken by the Ndam people in parts of Chad.
 E904331 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: Ndam language | Statement: [Sara languages, hasMember, Ndam language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ndam language
Context triple: [Sara languages, hasMember, Ndam language]
  • A. Damana language
    The Damana language is an indigenous Chibchan tongue spoken by the Wiwa people of the Sierra Nevada de Santa Marta region in northern Colombia.
  • B. Nawdm language
    The Nawdm language is a Gur language spoken primarily by the Nawda (Nawdm) people in parts of northern Togo and neighboring regions of West Africa.
  • C. Tai Dam language
    The Tai Dam language is a Southwestern Tai language spoken primarily by the Tai Dam (Black Tai) people in parts of Vietnam, Laos, Thailand, and China.
  • D. Nambya language
    Nambya is a Bantu language spoken primarily in northwestern Zimbabwe and northeastern Botswana, closely related to Kalanga and used by the Nambya people.
  • E. Nembe language
    The Nembe language is an Ijoid language spoken primarily by the Nembe people in Bayelsa State in Nigeria’s Niger Delta region.
  • 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: Ndam language
Triple: [Sara languages, hasMember, Ndam language]
Generated description
Ndam language is a Central Sudanic language spoken by the Ndam people in parts of Chad.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ndam language
Target entity description: Ndam language is a Central Sudanic language spoken by the Ndam people in parts of Chad.
  • A. Damana language
    The Damana language is an indigenous Chibchan tongue spoken by the Wiwa people of the Sierra Nevada de Santa Marta region in northern Colombia.
  • B. Nawdm language
    The Nawdm language is a Gur language spoken primarily by the Nawda (Nawdm) people in parts of northern Togo and neighboring regions of West Africa.
  • C. Tai Dam language
    The Tai Dam language is a Southwestern Tai language spoken primarily by the Tai Dam (Black Tai) people in parts of Vietnam, Laos, Thailand, and China.
  • D. Nambya language
    Nambya is a Bantu language spoken primarily in northwestern Zimbabwe and northeastern Botswana, closely related to Kalanga and used by the Nambya people.
  • E. Nembe language
    The Nembe language is an Ijoid language spoken primarily by the Nembe people in Bayelsa State in Nigeria’s Niger Delta region.
  • 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_69d6aa9a40d88190a373e2c7e48285db completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d799ed12d88190a4ad8c346d68f11f completed April 9, 2026, 12:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3e7d3043c8190bdbe0ec51992db0c completed April 18, 2026, 8:21 p.m.
NEDg Description generation batch_69e3f2cbb4708190a328cff473104d14 completed April 18, 2026, 9:08 p.m.
NED2 Entity disambiguation (via description) batch_69e3f497a01881909d1dae70a02e5f97 completed April 18, 2026, 9:16 p.m.
Created at: April 8, 2026, 9:27 p.m.